OFDM pilot tone tracking for wireless LAN

ABSTRACT

A pilot phase tracking loop for an OFDM receiver including a phase rotator for receiving an incoming signal, which is coupled to a Fourier transform, which is coupled to a pilot phase error metric for determining a phase error estimate associated with a received OFDM symbol, e.g., a data symbol. The pilot phase error metric is coupled to a loop filter, which is coupled to an oscillator, which is coupled back to the phase rotator. The phase rotator rotates the incoming signal by the filtered phase error estimate for subsequent OFDM symbols to reduce the phase noise of the signaling output from the phase rotator. Thus, the phase noise introduced by a radio portion of the OFDM receiver and an OFDM transmitter is compensated for by the pilot phase error estimation in the baseband portion of the OFDM receiver and improved OFDM signal tracking is accomplished under poor SNR conditions.

This application is a Continuation-In-Part (CIP) of U.S. applicationSer. No. 09/790,429, filed Feb. 21, 2001, entitled “OPTIMUM PHASE ERRORMETRIC FOR OFDM PILOT TONE TRACKING IN WIRELESS LAN”, the entirety ofwhich is hereby incorporated by reference.

This patent document relates to the following patent documents filedconcurrently herewith. The related patent documents, all of which areincorporated herein by reference, are: U.S. patent application Ser. No.09/935,081, of Crawford; entitled OFDM PILOT TONE TRACKING FOR WIRELESSLAN, Atty Docket No. 69903; and

U.S. patent application Ser. No. 09/935,083, of Crawford; entitled OFDMPILOT TONE TRACKING TO REDUCE PERFORMANCE LOSS DUE TO FREQUENCY PULLINGAND PUSHING; Atty Docket No. 70847.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates generally to orthogonal frequency divisionmultiplexed (OFDM)-based communications, and more specifically totracking pilot tones of OFDM-based communications to reduce phase noiserequirements in the radio portion of an OFDM receiver, as well asprovide nearly optimal frequency error tracking performance.

2. Discussion of the Related Art

In wireless local area network (WLAN) applications, multiple devicescommunicate with each other via OFDM-based radio frequency (RF) wirelesslinks. A common format for such OFDM communication is based upon theIEEE 802.11a standard or the HiperLAN2 standard, for example. Good localoscillator (LO) phase noise performance in the radio portion of the OFDMtransmitters and receivers is critical in such OFDM-based communicationswhen using complex signal constellations, such as 64-QAM and 256-QAM(quadrature amplitude modulation). This is because the symbol rate ischosen to be low enough to combat the severe multipath propagationcharacteristics that exist like those in indoor wireless applicationsand this low symbol rate also leads to greater phase noise relatedperformance impairment. For example, in IEEE 802.11a and HiperLAN2, thesymbol rate is approximately 250 kHz thereby accentuating the need tohave excellent phase noise performance in the radio at frequency offsetsfrom the carrier in the vicinity of 250 kHz and less.

Furthermore, the phase of the RF signaling is effected by phase noisegenerated in the local oscillators (LOs) of both the transmitter and thereceiver. Also, phase perturbations are introduced when the transmitteror the receiver physically moves relative each other and also when themultipath changes, e.g., a door is opened. Unfortunately, poor LO phasenoise performance leads to a potentially high symbol error rate, whichseriously degrades both the communication range and throughput of thesystem. For example, in a typical system using IEEE 802.11a, it isestimated that the acceptable phase noise interfering with eachsubcarrier of the OFDM waveform is on the order of 2.7 degrees rms.While this may be acceptable for QPSK and 16-QAM modulations, it isexcessive for 64-QAM modulation or higher constellations, resulting inconstellation points being easily confused.

Further adding to the problem is the fact that most transmitters andreceivers of such wireless products are highly integrated on a singledevice or chip. As such, the performance of the RF portion of thereceiver, for example, is relatively limited. Furthermore, implementingthe RF portion of the system to have the desired good phase noiseperformance that is required for higher order modulations, such as64-QAM and above, is very difficult when implemented on a single chipwith low supply voltages (e.g., 3.3 volts).

SUMMARY OF THE INVENTION

The present invention advantageously addresses the needs above as wellas other needs by providing a pilot tracking system utilizing an optimumpilot phase error metric based on a maximum likelihood estimationapproach in the baseband processing portion of the OFDM-based receiverto compensate for poor local oscillator performance in the radio portionof the OFDM-based receiver and transmitter and improve frequencytracking in general.

In one embodiment, the invention can be characterized as a pilot phasetracking loop for an orthogonal frequency division multiplexed (OFDM)receiver comprising a phase rotator for receiving an incoming signal, aFourier transform coupled to an output of the phase rotator and a pilotphase error metric coupled to an output of the Fourier transform fordetermining a phase error estimate associated with a received OFDMsymbol. A loop filter is coupled to an output of the pilot phase errormetric and an oscillator is coupled to an output of the loop filter. Theoscillator has an output coupled to the phase rotator for causing thephase rotator to rotate the incoming signal by the filtered phase errorestimate for subsequent OFDM symbols such that the phase noise of thesignaling output from the phase rotator is reduced.

In another embodiment, the invention can be characterized as a pilotphase tracking loop for an orthogonal frequency division multiplexed(OFDM) receiver comprising a phase rotator for receiving and adjustingthe phase of an incoming signal, a Fourier transform coupled to anoutput of the phase rotator and a pilot phase error metric coupled to anoutput of the Fourier transform. Also, a loop filter coupled to thepilot phase error metric and an oscillator coupled to the loop filterand having an output coupled to the phase rotator.

In yet another embodiment, the invention can be characterized as amethod for tracking pilot phase in an orthogonal frequency divisionmultiplexed (OFDM) receiver comprising the steps of: receiving anincoming signal corresponding to an OFDM preamble waveform at a Fouriertransform of the OFDM receiver; determining pilot reference pointscorresponding to a plurality of pilots of an OFDM preamble waveform;receiving an incoming signal corresponding to an OFDM symbol at theFourier transform; determining complex signal measurements correspondingto each of the plurality of pilots of the OFDM symbol; determining aphase error estimate corresponding to the OFDM symbol; filtering thephase error estimate; and rotating a phase of the incoming signal forsubsequent OFDM symbols to be received at the Fourier transform afterthe OFDM symbol by the filtered phase error estimate, wherein a phasenoise of the incoming signal for the subsequent OFDM symbols is reduced.

In a further embodiment, the invention can be characterized as a methodof pilot phase tracking in an orthogonal frequency division multiplexed(OFDM) receiver comprising the steps of: receiving an incoming signalrepresenting an OFDM waveform at a Fourier transform of the OFDMreceiver; determining a phase error estimate corresponding to an OFDMsymbol of the OFDM waveform based upon the output of the Fouriertransform; filtering the phase error estimate; and rotating a phase ofthe incoming signal for subsequent OFDM symbols to be received at theFourier transform after the OFDM symbol by the filtered phase errorestimate, wherein the phase noise of the incoming signal for thesubsequent OFDM symbols is reduced.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and other aspects, features and advantages of the presentinvention will be more apparent from the following more particulardescription thereof, presented in conjunction with the followingdrawings wherein:

FIG. 1 is a block diagram of an orthogonal frequency divisionmultiplexed (OFDM) receiver illustrating a phase noise contribution ofthe local oscillators (LO) of the radio portion of the OFDM receiver,and in which one or more embodiments of the invention may be practiced;

FIG. 2 is a diagram of the PHY-layer frame structure for the IEEE802.11a standard used in OFDM communications, for example, by the OFDMreceiver of FIG. 1;

FIG. 3 is a functional block diagram of a pilot tracking loop of abaseband processing portion of the OFDM receiver of FIG. 1, whichutilizes a pilot phase error metric based on a maximum likelihoodestimation approach for estimating the phase error of the OFDM datasymbols in accordance with one embodiment of the invention;

FIG. 4 is a functional block diagram of a pilot phase error metric ofthe pilot tracking loop of FIG. 3 which is based upon maximum likelihoodestimation in accordance with one embodiment of the invention;

FIG. 5 is a graph illustrating the LO phase noise contribution vs.frequency using no pilot tracking and pilot tracking according to theembodiment of FIGS. 3 and 4;

FIG. 6 is a flowchart of the steps performed in the pilot phase errormetric of FIG. 4 in accordance with one embodiment of the invention;

FIG. 7 is an illustration of the closed-loop transfer functions of thepilot tracking loop of FIG. 3 according to one embodiment;

FIG. 8 is a functional block diagram of a pilot tracking loop of thebaseband processing portion of the OFDM receiver of FIG. 1, whichincludes a phase error metric utilizing a maximum likelihood estimatorfor the phase error of OFDM data symbols in accordance with anotherembodiment of the invention;

FIG. 9 is a functional block diagram of the pilot phase error metric ofthe pilot tracking loop of FIG. 8 using an optimum maximum likelihoodestimation performed in accordance with one embodiment of the invention;

FIG. 10 is a functional block diagram of a discrete Fourier transformportion of the pilot phase error metric of FIG. 9 in accordance with yetanother embodiment of the invention;

FIG. 11 is an illustration of the closed-loop transfer functions of thepilot tracking loop 806 of FIG. 8 according to another embodiment;

FIG. 12 is a graph illustrating the LO phase noise contribution vs.frequency using no pilot tracking, pilot tracking according to theembodiment of FIGS. 3 through 4 and pilot tracking according to theembodiments of FIGS. 8 through 10;

FIG. 13 is a functional block diagram illustrating the loop filter ofthe pilot tracking loop of FIG. 8 according to one embodiment of theinvention;

FIG. 14 is a functional block diagram of a digital implementation of theloop filter of FIG. 13 according to another embodiment of the invention;

FIG. 15 is a functional block diagram illustrating a simulated versionof the digital loop filter of FIG. 14;

FIG. 16 is a graph illustrating the response of the simulated trackingloop filter of FIG. 15 as measured at the indicated probe points in FIG.15; and

FIG. 17 is a flowchart is shown of the steps performed to reduce theeffects of frequency pulling and frequency pushing according to anotherembodiment of the invention.

Corresponding reference characters indicate corresponding componentsthroughout the several views of the drawings.

DETAILED DESCRIPTION OF THE INVENTION

The following description is not to be taken in a limiting sense, but ismade merely for the purpose of describing the general principles of theinvention. The scope of the invention should be determined withreference to the claims.

Referring first to FIG. 1, a block diagram is shown of an orthogonalfrequency division multiplexed (OFDM) receiver illustrating the phasenoise contribution of the local oscillators (LO) of the radio portion ofthe OFDM receiver, and in which one or more embodiments of the inventionmay be practiced. The OFDM receiver 100 (also referred to as thereceiver 100) includes an antenna 102, a radio portion 104 and abaseband processing portion 106. The radio portion 104 includes localoscillators, shown collectively as local oscillator 108 (hereinafterreferred to as LO 108), which introduces phase noise, shown as noise110, into the receiver 100. The noise 110 is summed with the signalsfrom the local oscillator 108 (illustrated at summer 114) and multipliedwith the received signal at mixer 112. As is common, the received signalis converted from RF (radio frequency) to an incoming signal 116 (alsoreferred to as a “baseband/IF signal”) sent to the baseband processingportion 106. The incoming signal 116 may be a baseband signal (alsoreferred to as a “baseband I/Q signal”). In some embodiments, theincoming signal 116 may be an intermediate frequency signal (alsoreferred to as an IF signal) which is converted to baseband in thebaseband processing portion 106. The frequency translation from RF tobaseband can be done in multiple steps of frequency conversions. Assuch, the incoming signal 116 includes phase noise 110 as introduced bythe LO 108 of the radio portion 104 of the OFDM receiver 100. Inreality, the incoming signal 116 will also include phase noise asintroduced by the local oscillators at the OFDM transmitter thattransmits the OFDM signal to the receiver 100 as well as other noiseintroduced by the channel, e.g., changes in the multipath, movements ofthe receiver and transmitter relative to each other, and thermal noise.

One solution to reducing the phase noise contribution of the LO 108 isto design a radio portion 104 having good phase noise performancecharacteristics. However, in such an implementation where the radioportion 104 and the baseband processing portion 106 are integrated intoone or more devices (i.e., chips), the design of such a radio portion104 is difficult and costly, particularly as higher order modulationsare used.

In accordance with one embodiment of the invention, the specificationsof the radio portion 104 are relaxed such that a certain amount of phasenoise 110 introduced by the LO 108 is acceptable. Advantageously andaccording to one embodiment, the phase noise 110 introduced by the LO108 is compensated for by the baseband processing portion 106 of theOFDM receiver 100. Thus, the baseband processing portion 106 works toeffectively relax the phase noise performance requirements of the radioportion 104, which allows the radio portion 104 to be designedanticipating the poorer phase noise performance. Thus, the radio portion104 can be implemented more easily and inexpensively. The key to suchembodiments is understanding the relationship between both the radioportion 104 and the baseband processing portion 106. A typical approachmight be to optimally design the radio portion 104 and then optimallydesign the baseband processing portion 106. Such an approach leads to acomplex and expensive radio portion 104 requiring good phase noiseperformance. That is, the phase noise introduced by the LO 108 does notneed to be further corrected and is sufficient to support signaling atthe specified modulations. However, as the modulation constellationincreases, for example, moving from 16-QAM to 64-QAM to 256-QAM, lessand less phase noise introduced by the LO 108 can be tolerated.Otherwise, with such higher-order constellations, the same phase noiseintroduced by the LO 108 is more likely to result in constellationpoints being confused. Thus, as the modulation constellation increases,the specifications of the radio portion 104 become increasingly morestringent. Thus, a radio portion 104 with good phase noise performancebecomes more difficult and expensive to implement as the constellationcomplexity increases.

However, by relaxing the requirements of the radio portion 104 such thatthe radio portion 104 contributes phase noise 110 that might otherwiseresult in constellation point errors (possibly resulting in anunacceptable symbol error rate), a simpler and less expensive radioportion is implemented. Furthermore, advantageously the phase noisecontribution of the LO 108 is tracked and removed using a pilot trackingloop employing a maximum likelihood estimator in the baseband processingportion 106 of the receiver 100. Thus, the baseband processing portion106 effectively reduces the phase noise contribution of the LO 108 ofthe radio portion 104 without requiring that the radio portion 104 havegood phase noise performance. Thus, the baseband processing portion 106and the radio portion 104 are designed together to provide an integratedOFDM receiver 100 that is more easily implementable on a single deviceand that can support many symbol by symbol modulations, such as MPSK orM-ary QAM, e.g., constellations of 64-QAM or higher.

Further details regarding the specific techniques of using the basebandprocessing portion 106 to effectively reduce the phase noisecontribution of the LO 108 of the radio portion 104 are described below.

Referring next to FIG. 2, a diagram is shown of the PHY-layer framestructure for the 802.11a standard used in OFDM communications, forexample, by the OFDM receiver 100 of FIG. 1. Shown is a frame 200 havinga preamble 202 and a data portion 204. The preamble 202 includes a shortsymbol portion 206 including 10 short symbols (t₁-t₁₀) and a long symbolportion 208 including two long symbols (T₁ and T₂). The data portion 204includes multiple data symbols 210 (also referred to as OFDM symbols orsimply symbols). Each long symbol T₁ and T₂ and each data symbol 210having a guard time interval 212 preceding it. The frame 200 is alsoreferred to as a PHY-layer frame or a medium access control (MAC) frame.

According to these standards, the preamble 202 is chosen which is wellsuited to measuring frequency errors quickly in the communicationsystem, but is substantially less ideal for measuring precision time ofsignal arrival. As is well known in the art, the short symbol portion206 is used for signal detection, diversity selection, coarse frequencyoffset estimation, and timing synchronization. The long symbol portion208 is used for channel estimation and fine frequency offset estimation.Following the preamble 202, each OFDM symbol 210 consists of a properlytime-windowed set of modulated subcarriers (e.g., sine waves) and aguard time interval 212. As is well known in the art, this guard timeinterval 212 is utilized to allow the communication channel's transientto decay before transmitting the next OFDM symbol 210. According to theIEEE 802.11a standard, this guard time interval 212 is 0.8 μs and thesymbol 210 length is 3.2 μs. Note that the guard time interval in thelong symbol portion 208 is twice the duration of that preceding eachdata symbol 210, i.e., 1.6 μs. According to the HiperLAN2 standard, theguard time interval 212 is selectable between 0.4 μs or 0.8 μs while thesymbol 210 length is 3.2 μs. As such, the guard time interval 212 islong enough such that all reflections of the transmitted symbol 210 areadequately reduced prior to transmission of the next OFDM symbol 210.

As is well known in the IEEE 802.11a and the HiperLAN2 waveforms, eachsymbol, whether the data symbol 210 or one of the long symbols T₁ andT₂, includes 48 data bearing subcarriers and a plurality of pilotsubcarriers (also referred to as “pilot tones” or simply as “pilots”)buried within the signal that do not transport data, e.g., 4 pilots inthe IEEE 802.11a and HiperLAN2 waveforms. According to the IEEE 802.11astandard, these pilots occupy subcarrier positions ±7ΔF and ±21ΔF ofeach symbol. As such, the phase behavior of the pilots is preciselyknown aside from channel related impairments and LO phase noise. Sincethe phase noise imposed on these pilot tones is the same phase noisethat is imposed upon all of the subcarriers, it is possible to mitigatemuch of the LO phase noise by phase tracking these pilots. However,since finite signal-to-noise ratio (SNR) at the OFDM receiver input alsocontributes phase noise to all of the subcarriers, the effective noisebandwidth of the tracking algorithm can not be made arbitrarily large.Rather, the bandwidth of the tracking algorithm is based upon acompromise between LO-related phase noise suppression and additive noisedue to the finite input SNR.

According to one embodiment of the invention, during the long symbols T₁and T₂ of the long symbol portion 208, complex signal measurements aretaken for each pilot tone and stored in rectangular form as a respectivepilot reference point for each pilot tone of the MAC frame 200. Then, apilot phase error metric of a pilot tracking loop processes complexsignal measurements for all of the pilots of each subsequent data symbol210 along with the pilot reference points to produce an estimate of theaggregate phase error of the current OFDM data symbol as compared to theactual phase at the beginning of the MAC frame 200. The pilot phaseerror metric is based on a maximum likelihood estimation approach in howthe complex signal measurements of the pilots and the pilot referencepoints are combined. Advantageously, this embodiment estimates theaggregate phase error of the data symbol without having to explicitlycalculate the amplitude and phase of the individual pilots in the longsymbol portion 208 or calculate the amplitude and phase of theindividual pilots of each data symbol 210. Next, the estimation of theaggregate phase error of the current data symbol is then fed backthrough a loop filter and used to rotate the phase of the incomingbaseband IQ signal for the next OFDM data symbols so that they will bereceived with an improved phase error. This maximum likelihoodestimation-based approach in the pilot phase error metric is a departurefrom conventional methods in that it tracks the pilot aggregate of thedata symbols, rather than only tracking the strongest of the pluralityof pilots of the data symbols. Thus, the maximum likelihood pilot phaseerror metric compensates for the poor phase noise performance of theradio portion of the OFDM receiver. A natural by-product of the maximumlikelihood metric is that it also maximizes the effective SNR for thepilot symbols considered as a whole. The additional SNR permits greatersuppression of the LO phase noise by these disclosed techniques. Themaximum likelihood formulation automatically adjust the effectivecontribution made by each pilot even in the presence of frequencyselective fading, delivering the lowest variance phase error estimatepossible.

Referring next to FIG. 3, a functional block diagram is shown of a pilottracking loop 300 of the baseband processing portion of the OFDMreceiver of FIG. 1, which utilizes a pilot phase error metric based on amaximum likelihood estimation approach for estimating the phase error ofOFDM data symbols in accordance with one embodiment of the invention.Shown is the incoming signal 116 (which may be a baseband signal or anIF signal, for example), a phase rotator 302, an FFT 304 (fast Fouriertransform, which may be referred to generically as a “Fouriertransform”), a switch 306 having positions A (solid line) and B (dashedline), a reference point storage 308, a pilot phase error metric 310, apseudo random pilot modulation generator 312 (hereinafter referred to asa PN pilot modulation generator 312), a loop filter 314, a summation318, a coarse and fine frequency estimate signal 320 and an NCO 316(numerically controlled oscillator, which may be referred to genericallyas an “oscillator”).

The incoming signal 116 is input to the phase rotator 302. The phaserotator 302 is coupled to the FFT 304, which is coupled to the switch306. In position A, the switch 306 is coupled to the pilot referencestorage 308, which is coupled to the pilot phase error metric 310. Inposition B, the switch 306 is directly coupled to the pilot phase errormetric 310. The PN pilot modulation generator 312 is also coupled to thepilot phase error metric 310. Additionally, the loop filter 314 couplesthe pilot phase error metric 310 to the NCO 316 via the summation 318and the NCO 316 is coupled back to the phase rotator 302. The summation318 sums the output of the loop filter 314 with the coarse and finefrequency estimate signal 320, which is then output to the NCO 316.

In operation, the pilot tracking loop 300 (also referred to as aphase-locked loop) is used to track the phase changes of all of theplurality of pilots for each symbol in order to correct or minimize thephase error for subsequent data symbols relative to the reference pointsmeasured, for example, during the preamble. Initially, the pilottracking loop determines reference points for each of the respectivepilots since the amplitudes and phases of the received pilots arecompletely unknown and may vary from pilot to pilot within each symboldue to the multipath and the time of arrival. In one embodiment, thepilots of the long symbols T₁ and T₂ of the OFDM preamble waveform areused to determine the reference points. As such, when the long symbolsof the incoming signal 116 pass through the phase rotator 302, they areunchanged in phase since the pilot tracking loop is not yet activated,i.e., the switch 306 is in position A. During the long symbol portion ofthe preamble, a channel estimate is made by the FFT 304 and saved, e.g.,the complex signal measurements I+jQ for each pilot are extracted at theFFT 304 and saved in the reference point storage 308. The referencepoints for each pilot are saved in rectangular form as Uk and vk (wherek=0,1,2 and 3), which represent the I (in-phase) and Q (quadrature)values, respectively, for each pilot tone. During this time (i.e., whenthe switch 306 is in position A), the NCO 316 is preset to the properinitial conditions and the loop filter 314 updating is disabled.

After the pilot reference points u_(k) and v_(k) are determined for eachpilot using the FFT 304, the subsequent data symbols of the incomingsignal 116 are processed by the FFT 304 one at a time. The switch 306 isnow moved to position B, which activates the pilot tracking loop. Theoutputs of the FFT 304, i.e., complex signal measurements, correspondingto each of the pilots of the current data symbol are input to the pilotphase error metric 310 which is based upon a maximum likelihoodestimation approach using each of the pilots of the data symbol ascompared to the respective stored reference points u_(k) and v_(k) foreach pilot. The result of the pilot phase error metric 310 is anaggregate phase error estimate over the respective data symbol. Aspreviously mentioned, in this embodiment, the pilot phase error metric310 advantageously uses all of the pilots to produce its estimate. It isimportant that all of the pilots of each data symbol are tracked inorder to mitigate the effect of frequency selective fading over thefrequency range of the OFDM data symbol.

The loop filter 314 is updated based upon the output of the pilot phaseerror metric 310. Since the pilot phase error metric 310 and the loopfilter 314 track relatively small frequencies, the coarse/fine frequencyestimate signal 320 (obtained from the channel estimation process duringthe long symbols of the preamble at another portion of the OFDMreceiver) is summed with the output of the loop filter 314 at summation318. Thus, the loop filter 314 then modifies the NCO 316 which causesthe phase rotator 302 to de-rotate the incoming signal 116 to keep theaggregate phase error as low as possible. The loop filter 314, summation318 and the NCO 316 are well known components that may be found in manyphase-locked loops as known in the art.

Additionally, as is well known, the PN pilot modulation generator 312provides the pseudo random number sequence to remove the random BPSK(binary phase shift keying) modulation applied to each of the pilottones as given in the IEEE 802.11a standard.

The pilot tracking loop 300 includes phase rotator 302 for receiving andphase de-rotating the incoming signal 116, the switch 306, the referencepoint storage 308, the pilot phase error metric 310, the loop filter314, and the NCO 316 while advantageously utilizing the FFT 304 which isrequired within the OFDM receiver. It is also noted that in thisembodiment, the phase rotator 302 is provided before the FFT 304 in thereceiver such that the phase error is corrected prior to the FFT 304operation. In the event the incoming signal 116 comprises an IF signal,the phase rotator also converts this IF signal to a baseband signal or abaseband I/Q signal. Thus, whether the incoming signal 116 is a basebandsignal or an IF signal, the output of the phase rotator is a basebandsignal.

Referring next to FIG. 4, a functional block diagram is shown of thepilot phase error metric of the pilot tracking loop of FIG. 3 which isbased upon maximum likelihood estimation in accordance with oneembodiment of the invention. Shown is the pilot phase error metric 310including multiplexers 402 and 404, a maximum likelihood phaseerror/weighting processor 406, a quality estimator 408, a phase errorestimator 410, and a random pilot modulation removal 412. Also shown arethe PN pilot modulation generator 312 and the reference point storage308 which includes a u_(k) storage 414 and a Vk storage 416. Input I andQ samples from the FFT 304 for the respective pilots of the OFDM datasymbols are illustrated as signals 418 and 420 for pilot #0, signals 422and 424 for pilot #1, signals 426 and 428 for pilot #2, and signals 430and 432 for pilot #3.

Again, as the long symbol portion of the incoming baseband signal isprocessed by the FFT, the frequency bins of the FFT that correspond tothe four pilots of the long symbols are saved as u_(k) and v_(k) withinthe uk storage 414 and the v_(k) storage 416, where k=0,1,2 and 3. Thus,u_(k) and v_(k) are complex signal measurements in rectangular form foreach pilot that represent the reference points in IQ space for each ofthe four pilots (i.e., pilot #0, pilot #1, pilot #2 and pilot #3). Thesepilot reference points are saved for use in the maximum likelihood phaseerror/ weighting processor 406.

The information from the FFT operation can be represented as A_(k)(amplitude of the k^(th) pilot subcarrier) and θ_(k) (phase of thek^(th) pilot subcarrier). If the discontinuous nature of the OFDM symbolsubcarriers is ignored, the k^(th) pilot tone can be represented as:

r _(k)(t)=A _(k) s _(k)(t)e ^(jθ) ^(_(k)) ^((t)) +n _(k)(t)  Eq. (1)

where r_(k)(t) is the received signal, S_(k)(t) is the transmittedsignal and n_(k)(t) represents complex Gaussian noise having a two-sidedpower spectral density of N_(o)/2 W/Hz. Thus, the beginning of thepilot-bearing OFDM signal train for a given OFDM symbol and pilot toneis represented as:

 r _(k)(0)=A _(k) s _(k)(0)e ^(jθ) ^(_(k)) ⁽⁰⁾ +n _(k)(0)=u _(k) +jv_(k)  Eq. (2)

Next, after having stored the reference points, the pilot phase trackingloop is activated, e.g., the switch 306 of FIG. 3 is moved to positionB. During the subsequent data portion of the MAC frame, each rk(t)changes with time from data symbol to data symbol over the framestructure. Generally, it is desired to track the pilots having a largeramplitude because they are less influenced by the additive Gaussiannoise of the receive channel, and also the channel phase nearfrequency-selective spectrum nulls will be erratic. Thus, the sampledtracking loop tracks the nominal pilot subcarrier phase departure fromthe phase of the reference point at the beginning of the frame structurefor each pilot.

As such, the pilot tracking loop is activated and the complex signalmeasurements (Is and Qs) from the FFT corresponding to each of therespective pilots #0 through #3 for each subsequent data symbol arecoupled to the respective one of multiplexers 402 and 404 to be inputinto the maximum likelihood phase error/weighting processor 406. It isnoted that the pilot reference points are stored in rectangular form asu_(k) and v_(k) and that the amplitude and phase of each of the pilotreference points is not actually calculated. It is also noted that thesubsequent data symbol by data symbol complex signal measurements of thein-phase and quadrature terms for the same pilot tones during the restof the burst reception are labeled as I_(k,m) and Q_(k,m), where m isthe data symbol time index. For example, the I_(k,m) values from the FFToperation for each data symbol are coupled to multiplexer 402 while theQ_(k,m) values from the FFT operation for each data symbol are coupledto multiplexer 404. The multiplexers 402 and 404 function to buffer theI_(k,m) and Q_(k,m) values to the maximum likelihood phaseerror/weighting processor 406. Thus, the maximum likelihood phaseerror/weighting processor 406 serially processes one set of I_(k,m) andQ_(k,m) values at a time such that redundant gates are not required tosimultaneously perform the steps in the maximum likelihood phaseerror/weighting processor 406 in parallel.

The initial relative phase of each pilot subcarrier at the beginning ofthe frame can be largely removed by modifying r_(k)(t) of Eq. (1) fort>0 per

rm _(k)(t)=r _(k)(t)e ^(−jθ) ^(_(k)) ⁽⁰⁾  Eq. (3)

where rm_(k)(t) represents the k^(th) pilot after removal of the phaseinitial estimate for the particular pilot during the long symbol portionof the preamble. Substituting Eq. (3) in Eq. (1):

n _(k)(t)=rm _(k)(t)−A _(k) s _(k)(t)e ^(j[θ) ^(_(k)) ^((t)−θ) ^(_(k))^((0)])

 =rm _(k)(t)−A _(k) s _(k)(t)e ^(jφ) ^(_(e)) ^((t))   Eq. (4)

where φ_(e) is the actual pilot phase error of the k^(th) pilot of thedata symbol relative to the pilot reference point, which is notexplicitly calculated, but is assumed to be the same for all of thepilots of a given data symbol. In the OFDM waveform, the MAC frame timeduration is purposely chosen such that the channel characteristicschange very little over an individual MAC frame. Therefore, for aspecific MAC frame, it is assumed that |A_(k)s_(k)(t)|=A_(k), aconstant. Thus, while the amplitudes of the individual pilots may bedifferent from each other, the amplitude of each pilot (A_(k)) fromsymbol to symbol will stay approximately constant over the course of theMAC frame. Since the pilot tracking loop of this embodiment primarilytracks phase rather than signal amplitude, some error in signalamplitude is acceptable.

The probability density function for an individual noise sample n_(k) isgiven by $\begin{matrix}{{{pdf}\left( n_{k} \right)} = {\frac{1}{2\pi \quad \sigma^{2}}\exp \left\{ {- \frac{n_{kc}^{2} + n_{ks}^{2}}{2\sigma^{2}}} \right\}}} & \text{Eq.~~(5)}\end{matrix}$

where n_(kc) and n_(ks) are the real and imaginary parts of the k^(th)bin noise sample n_(k) and σ is the standard deviation of the Gaussiannoise. Computing the log-likelihood function from Eq. (5), and thenmaximizing it, the maximum-likelihood estimator for the actual pilotphase error θ for a data symbol is given by: $\begin{matrix}{\hat{\theta} = {\tan^{- 1}\left\{ \frac{\sum\limits_{k}{A_{k}{{Im}\left( {rm}_{k} \right)}}}{\sum\limits_{k}{A_{k}{{Re}\left( {rm}_{k} \right)}}} \right\}}} & \text{Eq.~~(6)}\end{matrix}$

where {circumflex over (θ)} is the estimate of the aggregate pilot phaseerror of a data symbol relative to the reference points looking at allof the pilots of the data symbol together.

Generally, the sum $\sum\limits_{k}A_{k}^{2}$

will be nearly equal to a constant due to the AGC (automatic gaincontrol) action that precedes the A/D converter in the basebandprocessing portion. If the receive channel is flat (i.e., no frequencyselective fading present), then the Ak terms will all have the samevalue and Eq. (6) reduces to the classical maximum-likelihood estimatorthat is commonly seen for carrier phase.

In rectangular form instead of polar form, the complex signalmeasurements corresponding to the k^(th) pilot of the m^(th) data symbolare represented as:

r _(k,m) =I _(k,m) +jQ _(k,m)  Eq. (7)

where k=0,1,2 and 3. The phase rotation for the k^(th) pilot that mustbe applied to remove the phase argument as computed by the channelestimation process (i.e., the storage of u_(k) and V_(k)) can beexpressed as: $\begin{matrix}{^{- {{j\theta}_{k}{(0)}}} = \frac{u_{k} - {jv}_{k}}{\sqrt{u_{k}^{2} + v_{k}^{2}}}} & \text{Eq.~~(8)}\end{matrix}$

where e^(−jθ) ^(_(k)) ⁽⁰⁾ is found in Eq. (3). Thus, rm_(k,m) for them^(th) data symbol becomes: $\begin{matrix}{{rm}_{k,m} = {\left( {I_{k,m} + {jQ}_{k,m}} \right)\left( \frac{u_{k} - {jv}_{k}}{\sqrt{u_{k}^{2} + v_{k}^{2}}} \right)}} & \text{Eq.~~(9)}\end{matrix}$

where rm_(k,m) represents the signal measurement of the k^(th) pilotafter removal of the phase initial estimate, which is not explicitlycalculated.

According to this embodiment of the maximum likelihood estimation basedapproach which tracks all of the pilots of the OFDM data symbol, eachpilot signal contribution of Eq. (9) is then weighted by the signalamplitude A_(k) of the k^(th) pilot. Even though the amplitudes A_(k)are time varying, they generally do not vary over the duration of theMAC frame such that A_(k)(t) approximates the A_(k) measurement at thebeginning of the MAC frame, e.g., from the reference points u_(k)+jv_(k)of the long symbol duration. Thus, the amplitude to weight each of thepilot contributions is given by: $\begin{matrix}{{{A_{k}(t)} \approx {A_{k}(0)}} = \sqrt{u_{k}^{2} + v_{k}^{2}}} & \text{Eq.~~(10)}\end{matrix}$

Multiplying Eq. (9) by Eq. (10), the quantity A_(k)rm_(k,m) is a complexsignal given by:

 A _(k) rm _(k,m) =[u _(k) I _(k,m) +v _(k) Q _(k,m) ]+j[u _(k) Q _(k,m)−v _(k) I _(k,m)]  Eq. (11)

Summing the each of the complex signals A_(k)rm_(k,m) for the k pilotsproduces a complex composite signal looking at all of the pilots of adata symbol together and is given by: $\begin{matrix}{{\sum\limits_{k = 0}^{3}{A_{k}{rm}_{k,m}}} = {\sum\limits_{k = 0}^{3}\left\lbrack {\left( {{u_{k}I_{k,m}} + {v_{k}Q_{k,m}}} \right) + {j\left( {{u_{k}Q_{k,m}} - {v_{k}I_{k,m}}} \right)}} \right\rbrack}} & \text{Eq.~~(12)}\end{matrix}$

Thus, based upon Eq. (6), the aggregate phase error estimate for them^(th) data symbol, {circumflex over (θ)}_(m), is the argument of thecomplex composite signal for all pilots together,${\sum\limits_{k = 0}^{3}{A_{k}{rm}_{k,m}}},$

which is represented mathematically by: $\begin{matrix}{{\hat{\theta}}_{m} = {\arg \left( {\sum\limits_{k = 0}^{3}{A_{k}{rm}_{k,m}}} \right)}} & \text{Eq.~~(13)}\end{matrix}$

It is noted that Eq. (13) must be adjusted to deal with the randombi-phase modulation of the pilot subcarriers during the frame; however,the quantity in Eq. (13) is the estimate that is produced by the pilotphase error metric, and is further shown in more detail below as Eq.(14).

The argument of the complex composite signal (i.e., Eq. (13)) isdetermined by the phase error estimator 410 and is based upon themaximum likelihood estimation approach of Eq. (6), which is re-writtenbelow in Eqs. (14) through (16). Preferably, using a cordic-basedarctangent method on the real and imaginary parts of the complexcomposite signal in the phase error estimator 410, the output of thephase error estimator 410 is given by Eq. (14). In alternativeembodiments, making use of the small angle approximation within thephase error estimator 410, Eq. (14) can be recast as Eqs. (15) and (16):$\begin{matrix}{{\hat{\theta}}_{m} = {\tan^{- 1}\left\lbrack \frac{\sum\limits_{k = 0}^{3}\left( {{u_{k}Q_{k,m}} - {v_{k}I_{k,m}}} \right)}{\sum\limits_{k = 0}^{3}\left( {{u_{k}I_{k,m}} + {v_{k}Q_{k,m}}} \right)} \right\rbrack}} & \text{Eq.~~(14)} \\{\cong {\sin^{- 1}\left\lbrack \frac{\sum\limits_{k = 0}^{3}\left( {{u_{k}Q_{k,m}} - {v_{k}I_{k,m}}} \right)}{\sum\limits_{k = 0}^{3}\left( {{u_{k}I_{k,m}} + {v_{k}Q_{k,m}}} \right)} \right\rbrack}} & \text{Eq.~~(15)} \\{\approx \frac{\sum\limits_{k = 0}^{3}\left( {{u_{k}Q_{k,m}} - {v_{k}I_{k,m}}} \right)}{\sum\limits_{k = 0}^{3}\left( {{u_{k}I_{k,m}} + {v_{k}Q_{k,m}}} \right)}} & \text{Eq.~~(16)}\end{matrix}$

where {circumflex over (θ)}_(m) is the aggregate phase error of them^(th) data symbol relative to the pilot reference points at thebeginning of the OFDM MAC frame. Thus, the maximum likelihood/ weightingprocessor 406 calculates the quantities in the numerator and thedenominator of Eqs. (14) through (16) while the quantity {circumflexover (θ)}_(m) of Eqs. (14) through (16) is determined in the phase errorestimator 410. The quantities in the numerator and the denominator orEqs. (14) through (16) are weighted averages producing composite I and Qsignals that represent the deviation of the pilots of the current datasymbol compared to the reference points measured at the beginning of theframe.

With the AGC present and the fact that the actual pilot phase error θfor a data symbol will be kept small by the pilot tracking loop, it cansuffice to use the small angle approximation and use only the numeratorportion of Eq. (6) for the pilot tone phase error metric as$\begin{matrix}{\hat{\theta} \approx {\sum\limits_{k}{A_{k}{{Im}\left( {rm}_{k} \right)}}}} & \text{Eq.~~(17)}\end{matrix}$

Again, it is noted that the random bi-phase modulation applied to thepilots at the OFDM transmitter is removed by the random pilot modulationremoval 412, which uses a pseudo random sequence which is known a priorifrom the PN pilot modulation generator 312. Thus, the output of therandom pilot modulation removal 412 is the aggregate phase error of theprocessed data symbol, {circumflex over (θ)}_(m).

As previously described, the multiplexers 402 and 404 buffer the I and Qsamples for each pilot of the symbol received from the FFT operation.Thus, when the maximum likelihood phase error/weighting processor 406calculates the numerator and denominator of Eqs. (14) through (16), itonly processes one pilot at a time. This reduces the overall gate countin a design implemented in a chip. However, it is noted that redundantgates may be used in place of the multiplexers 402 and 404 in otherembodiments. Additionally, all calculations done within the maximumlikelihood phase error/weighting processor 406 are done in rectangularform, instead of in polar form, for simplification reasons.

As shown above, advantageously, the pilot phase error metric 310 doesnot actually calculate the amplitude or phase of the individual pilotreference points, nor does it calculate the amplitude and phase ofindividual pilots of each subsequent data symbol. Likewise, the pilotphase error metric 310 does not actually calculate the relative phaseerror of individual pilots of each data symbol compared to each pilotreference point. The pilot phase error metric 310 advantageously usespre-signal detection combining techniques to combine the complex signalmeasurements (from the FFT operation) of the pilots to be used as thepilot reference points and the complex signal measurements of the pilotsof each subsequent data symbol in such a way that a complex compositesignal is generated prior to signal detection. This complex compositesignal represents a weighted pilot phase error for the aggregate of thepilots of the m^(th) data symbol relative to the pilot reference points.Thus, the maximum likelihood phase error/weighting processor 406determines the composite signals for the numerator and denominator ofEq. (14).

Furthermore, the phase error estimator 410 performs the signal detectionby computing the arctangent in Eq. (14) to obtain the aggregate phaseerror for the m^(th) data symbol. Thus, by advantageously combining thecomplex signal measurements in the maximum likelihood phaseerror/weighting processor 406 prior to the signal detection in the phaseerror estimator 410, a processing gain of approximately 10 log₁₀ n(where n is the number of pilots) is realized in comparison toperforming signal detection on each individual pilot of the data symboland then averaging them to obtain the aggregate phase error of the datasymbol, e.g., approximately 6 dB in the 4 pilot case. In other words,signal detection on the individual pilots would amount to estimating theamplitude and phase of each pilot of the data symbol in order todetermine a phase error for each pilot and then averaging the phaseerrors to determine the aggregate phase error for the entire datasymbol. Thus, in one embodiment, the pilot phase error metric 310performs pre-signal detection combining.

Additionally, as described above, the phase error estimator 410determines the phase angle of the aggregate phase error {circumflex over(θ)}_(m) or phase noise of the signaling, a potentially large portion ofwhich is due to the phase noise contribution of the LO of the radioportion of the OFDM receiver. A preferred approach is to use acordic-based arctangent method (see Eq. (14)) and an alternativeapproach is to use a small angle approximation (see Eq. (16)). Thecordic-based arctangent approach does not require large bit-widthmultiplications. It only shifts and adds. The small angle approximationshould be faster than the cordic-based arctangent approach, but itinvolves large bit width multiplication or division and is more prone todifficulties with the numerical dynamic range.

In one embodiment, the cordic-based arctangent approach is implementedsuch that the cordic iteration is performed between 8 and 15 times.Cordic-based arctangent methods are well known in the art, thus, nofurther explanation is required.

Thus, the pilot phase error metric 310 advantageously provides a maximumlikelihood estimation based approach for the pilot phase error relativeto the pilot reference points for all of the pilots of the OFDM symbols.According to one embodiment, it is important to track all of the pilotsto reduce the effects of frequency selective fading across the OFDMsymbols and reduce the variance of the estimator as well. For example,the phase may not change uniformly for all of the pilots as the channelconditions change. A single pilot may have the strongest SNR (e.g., thehighest amplitude) and its phase changes noticeably from symbol tosymbol; however, the phase of the other pilots may remain unchanged, orhave changed only slightly, from symbol to symbol. These other pilotsmay also continue to have a lower amplitude than the amplitude of thestrongest pilot. As such, due to frequency selective fading, thestrongest pilot does not accurately reflect the phase characteristics ofthe entire OFDM data symbol. However, by tracking and performing amaximum likelihood based estimation using all of the pilots, a moreaccurate picture of the signal phase across the OFDM symbol is estimatedsuch that the phase contribution due to the multipath and alsointroduced by the LO of the OFDM radios can be minimized. Furthermore,by keeping the phase error minimized, it is possible to use higher ordermodulations, such as M-ary QAM, e.g., 64-QAM or 256-QAM, without severeperformance degradation. It is noted that several of the embodiments ofthe invention will reduce this phase error for many symbol by symbolmodulations, such as MPSK and M-ary QAM.

Further advantageously, a natural by-product of the maximum likelihoodmetric of this embodiment is that it also maximizes the effective SNRfor the pilot symbols considered as a whole. The additional SNR allowsenhanced phase noise tracking resulting in greater suppression of the LOphase noise.

Additionally, the quality estimator 408 calculates a measure of thepilot tracking loop's quality, which is required elsewhere in the signalprocessing of the OFDM receiver. A convenient measure is the total powerpresent in the 4 pilot subcarriers of each symbol given by:$\begin{matrix}{P_{T} = {\sum\limits_{k = 0}^{3}\left\lbrack {u_{k}^{2} + v_{k}^{2}} \right\rbrack}} & {{Eq}.\quad (18)}\end{matrix}$

Note that the quality estimator 408 may be integrated with the maximumlikelihood phase error/weighting processor 406.

It is noted that Eqs. (12) through (16) and Eq. (18) are specificallyfor a waveform having 4 pilots (k=0,1,2 and 3); however, these equationsmay be written more generally for a waveform having n pilots with thesummation term expressed as $\sum\limits_{k = 0}^{n - 1}.$

Referring next to FIG. 5, a graph is shown illustrating the LO phasenoise contribution vs. frequency offset in Hz using no pilot trackingand pilot tracking according to the embodiment of FIGS. 3 and 4. Line502 represents the LO phase contribution spectrum without pilot trackingtechniques synthesized at 4 GHz. Note that the graph of FIG. 5 does notinclude channel additive Gaussian noise. For example, it is estimatedthat in an embodiment where the radio portion is highly integrated, theachievable phase noise performance in a free running on-chip VCO may beapproximately −78 dBc/Hz at 10 kHz offset. Thus, with the IEEE 802.11awaveform, the integrated phase noise interfering with each subcarrier ison the order of 2.7 degrees rms, which is excessive for 64-QAM andabove. In general, in one embodiment, the achievable phase noiseperformance in a free running on-chip VCO is greater than about −80dBc/Hz at 10 kHz offset. Also, in one embodiment, it is noted that phasenoise is present in both the transmitter and receiver ends and thatabove about 1.5 degrees rms, the integrated phase noise interfering witheach subcarrier at the receiver end becomes excessive for 64-QAMcommunications.

Line 504 represents the phase noise contribution spectrum of the LO ofthe radio portion with the pilot phase tracking of the embodimentsdescribed above, such that the phase noise contribution is significantlyreduced, particular at lower frequency offsets. Thus, it is estimatedthat the integrated phase error interfering with each subcarrier can besubstantially improved, the actual amount being a function of the signalconstellation type and the prevailing channel SNR.

Referring next to FIG. 6, a flowchart is shown for the steps performedby the pilot phase error metric in accordance with one embodiment of theinvention. Initially, the pilot reference points are determined for eachpilot subcarrier of the OFDM waveform (Step 602). These reference pointsu_(k) and v_(k) are the complex reference points within IQ space whichrepresent the respective pilots and are determined, in one embodiment,by taking the output of the FFT operation for each of the pilots of thelong symbol portion of the preamble of the IEEE 802.11a waveform. Thus,these pilot reference points are received into the pilot phase errormetric 310 of FIG. 3. This is performed when the pilot tracking loop ofFIG. 3 is not activated, for example, the switch 306 of FIG. 3 is inposition A. Next, these reference points are saved (Step 604), forexample, in the reference point storage of FIGS. 3 and 4.

In another embodiment, the pilot reference points may be obtained bytaking the output of the FFT operation for each of the pilots of aparticular data symbol (e.g., data portion 204 of FIG. 2) within thedata symbol portion of the MAC frame (e.g., data portion 204 of FIG. 2),rather than from the long symbol portion of the preamble. In someembodiments, the length of the data portion may be signifcantly longerin duration than that specified in the IEEE 802.11a standard and mayrequire new pilot reference points to be obtained from within the dataportion. For example, in such cases, the phase of the data symbols inthe middle or near the end of the data portion may be quite differentrelative to the pilot reference points measured during the preamble.Thus, it may be desired to obtain new pilot reference points fromlocations within the data portion of a MAC frame to compare with thepilots for subsequent data symbols. Thus, the pilot reference points maybe obtained using pilots of symbols from the preamble or from pilot fromsymbols in the data portion of a MAC frame.

Next, as the subsequent data symbols of the OFDM MAC frame enter thebaseband processing portion of the OFDM receiver, the pilot trackingloop is activated (e.g., switch 306 of FIG. 3 is now in position B). Assuch, complex signal measurements are determined in the FFT operationfor each of the plurality of pilots for a subsequent data symbol, ormore generically, a subsequent symbol (Step 606). In one embodiment,these complex signal measurements are received at the pilot phase errormetric of FIG. 3. This is done by taking the outputs of the frequencybins of the FFT operation corresponding to the respective pilotsubcarriers.

Next, the pilot phase error metric performs pre-detection combining andcomputes a complex signal for each pilot of the subsequent data symbolbased upon the pilot reference points and the complex signalmeasurements for the pilots of the subsequent data symbol (Step 608).For example, the complex signal for each pilot of the subsequent datasymbol is given by Eq. (11). Next, the complex signals are summed toproduce a complex composite signal (Step 610). For example, the complexcomposite signal for the subsequent data symbol is represented in Eq.(12). It is noted that the pilot phase error metric deals strictly withvectors and thus, no phase is actually determined at this point, i.e.,signal detection has not yet occurred.

Next, the aggregate pilot phase error for the subsequent data symbol isestimated (Step 612). This estimate is obtained by determining theargument of the complex composite signal, for example, as given in Eq.(13). The argument of the complex composite signal is determined asguided by Eq. (6) in the phase error estimator 410 of FIG. 4 and may bedone using a cordic-based arctangent approach (see Eq. (14)) or a smallangle approximation approach (see Eqs. (15) and (16)). Note that signaldetection occurs during Step 612, for example, in the arctangentoperation. Thus, Steps 602 through 612 apply a pilot phase error metricbased on a maximum likelihood-based estimation that advantageouslytracks all of the pilots for each data symbol of the OFDM waveform.

It is noted that this estimate must be modified to remove the pseudorandom modulation present on the pilots. For example, this is removed atthe random pilot modulation removal 412 of FIG. 4, which uses the PNpilot modulation generator 312.

Next, the estimate of the aggregate phase error is used to modify thepilot tracking loop and then Steps 606 through 614 are repeated untilthe end of the MAC frame (Step 614). This is done by the updating theloop filter 314 of FIG. 3, which adjusts the NCO 316 of FIG. 3. The NCO316 causes the phase rotator 302 of FIG. 3 to de-rotate the incomingbaseband signal 116 to minimize the phase error of the next symbols,e.g., the next data symbols. Then Steps 606 through 614 are repeated forthe next OFDM data symbol (or more generally, the next OFDM symbol) inan iterative fashion.

In one embodiment, Steps 602, 606, 608 and 610 are performed by themaximum likelihood phase error/weighting processor 406 of FIG. 4. Step612 is performed by the phase error estimator 410 of FIG. 4.Conveniently, all of the calculations of the maximum likelihood phaseerror/weighting processor 406 are carried out in rectangular form tosimplify the implementation.

The steps of FIG. 6 are typically performed as a set of instructionsthat are performed in dedicated hardware for optimum speed in thecalculations or in software using a processor or other machine toexecute the instructions to accomplish the given steps. Ideally, thesteps of FIG. 6 are performed by the pilot tracking loop of the basebandprocessing portion of an OFDM receiver having a pilot phase error metricand utilizing the FFT operation of the OFDM receiver. Additionally, thebaseband processing portion and the radio portion of the OFDM receivermay be integrated on to one or more devices or chips.

Next, generally referring to the pilot tracking loop 300 of FIG. 3, inoperation and according to one embodiment, the FFT 304 must wait toreceive all of the samples of a given data symbol before it beginsprocessing them. Then, the FFT 304 processes the samples in order toproduce the complex signal measurements that are input to the pilotphase error metric 310. Then, the pilot phase error metric 310 processesthese complex signal measurements as described with reference to FIGS.4-6. Once an estimate of the aggregate phase error is obtained, the loopfilter 314 is updated which causes the NCO 316 to make adjustments tothe phase rotator 302 to minimize the phase error for subsequent datasymbols. Thus, in addition to having to wait the entire 3.2 μsec lengthof each subsequent data symbol before the FFT 304 may begin processing,it is estimated that the total processing delay in the FFT 304 and thepilot phase error metric 310 is about another 3 μsec. This overall delayof about 6 μsec negatively impacts the maximum allowable closed-loopbandwidth of the pilot tracking loop 300.

Due to this delay, the optimum transient response performance (i.e.,dead-beat response in only two samples) according to one embodiment ofthe pilot tracking loop of FIG. 3 occurs when ω_(n)T=1 and dampingfactor ζ=0.75 are selected. This choice also corresponds to the maximumclosed-loop bandwidth achievable in the sampled control pilot trackingloop. For example, the maximum closed-loop bandwidth is approximately 40kHz for the 250 kHz OFDM symbol rate (of the IEEE 802.11a and HyperLAN2standards). While this tracking loop bandwidth is sufficient to trackand reduce local oscillator phase noise at small frequency offsets, itis too small to help reduce local oscillator phase noise at largerfrequency offsets, for example, frequency offsets in the 100 kHz range,as is illustrated in FIG. 7 below.

Briefly referring to FIG. 7, an illustration is shown of the closed-looptransfer functions of the pilot tracking loop as shown in FIG. 3. The LOphase noise transfer function 704 and the pilot tracking loop phasenoise transfer function 702 are illustrated, when the update rate is 250kHz (i.e., 1/4.0 μsec), and when ω_(n)T=1 (i.e., (on is about 13.9 kHz)and a damping factor ζ=0.75 are selected, which corresponds to a maximumclosed loop tracking bandwidth of 40 kHz. It is noted that thisillustration does not include additive Gaussian noise. As can be seen,at frequency offsets of about 40 kHz, since the gain margin for thisoptimum transient response is only about 2.5 dB, noise peaking ratherthan suppression happens near the edge of the tracking loop bandwidth.This noise peaking is on the order of about 10 dB, which actuallyworsens the phase noise performance and increases the likelihood ofsymbol errors at larger frequency offsets. In general, smaller closedloop bandwidths must be used for this reason.

Referring next to FIG. 8, a functional block diagram is shown of a pilottracking loop of the baseband processing portion of the OFDM receiver ofFIG. 1, which includes a pilot phase error metric utilizing a maximumlikelihood estimator for the phase error of OFDM data symbols inaccordance with another embodiment of the invention. Shown are theincoming signal 116, the phase rotator 302, a baseband signal 810 whichis ouput from the phase rotator 302, a cyclic prefix removal 802, theFFT 304, and a channel estimator 804. Also shown is a pilot trackingloop 806, which includes the phase rotator 302, a pilot phase errormetric 808 (also referred to as the phase error metric), the loop filter314, the summation 318, the coarse and fine frequency estimate signal320 and the NCO 316. Also shown is the PN pilot modulation generator312.

The incoming signal 116 is input to the phase rotator 302. As describedabove, the incoming signal 116 may be a baseband signal or an IF signal.The output of the phase rotator 302, i.e., the baseband signal 810 orbaseband I/Q signal, is coupled to both the cyclic prefix removal 802and the pilot phase error metric 808. The output of the cyclic prefixremoval 802 is coupled to the FFT 304, which is coupled to the channelestimator 804. It is noted that in some embodiments, the cyclic prefixremoval 802 occurs before the phase rotator 302, such that the output ofthe phase rotator 302 is coupled directly to the FFT 304. Thus, thecyclic prefix removal 802 is an optional functional componentillustrated in dashed lines. Furthermore, in some embodiments and as isknown in the art, there may be other functional modules or processingoperations that occur in between the phase rotator 302 and the FFT 304in place of or in addition to the cyclic prefix removal 802. Within thepilot phase tracking loop 806, the output of the pilot phase errormetric 808 is coupled to the loop filter 314, which is coupled to theNCO 314, which is coupled back to the phase rotator 302. Since the pilotphase error metric 310 and the loop filter 314 track relatively smallfrequencies, the output of the loop filter 314 is summed at summation318 with the coarse and fine frequency estimate signal 320. The coarseand fine frequency estimate signal 320 is commonly derived at thechannel estimator 804. The pilot phase error metric 808 is also coupledto the NCO 314 in order to preset the NCO 314. The PN pilot modulationgenerator 312 is coupled to the pilot phase error metric 808.

Advantageously in this embodiment, rather than using the FFT 304 toprocess and produce the complex signal measurements needed for the pilotphase error metric, the pilot phase error metric 808 generates thecomplex signal measurements itself. This reduces the processing delaythat occurs while waiting for the FFT operation to be completed, whichwill increase the allowable closed-loop bandwidth.

Although the improved pilot tracking loop 806 does not utilize the FFT304, the FFT 304 is still part of the OFDM baseband processing portionof the OFDM receiver. As shown, the incoming signal 116 passes throughthe phase rotator 302. In this embodiment, the output of the phaserotator 302 goes through the cyclic prefix removal 802 prior to enteringthe FFT 304. The cyclic prefix removal 802 removes the guard timeinterval prepended to each OFDM symbol. However, it is noted that theoutput of the phase rotator 302 may be directly routed to the FFT 304,the cyclic prefix removal occurring elsewhere. It is also understoodthat other functional modules or processing steps may be located inbetween the phase rotator 302 and the FFT 304, in place of or inaddition to the cyclic prefix removal 802. The FFT 304 continues toprocess the baseband IQ signal. For example, according to IEEE 802.11aand HiperLAN2, the channel estimator 804 utilizes the outputs of the FFT304 to determine the initial course frequency estimate from shortsymbols (e.g., ti through t₁₀) of the OFDM preamble and the finefrequency estimate from the long symbols (e.g., T₁ and T₂) of the OFDMpreamble. This information is used to generate the coarse and finefrequency estimate signal 320 needed in the pilot tracking loop 806.

Instead of relying on the FFT 304 to generate the complex signalmeasurements needed for the pilot phase error metric 808, the output ofthe phase rotator, i.e., the baseband signal 810, is routed to both theFFT 304 (e.g., through the cyclic prefix removal 802) and the pilotphase error metric 808 of the pilot tracking loop 806 in parallel paths,i.e., path A and path B. This embodiment of the pilot tracking loop 806is a departure from those known in the art. The fact that the incomingsignal 116 is phase de-rotated prior to the FFT operation is unique.Most pilot tracking techniques take place and adjust the phase after theFFT operation. Furthermore, processing the baseband signal 810 inparallel paths, shown as path A and path B, with the FFT 304 is unique.Again, in known OFDM receivers, pilot tracking, if present occurs afterthe completion of the FFT operation, not in a parallel path to the FFToperation. Thus, the presence of path B for pilot tracking is not knownin the existing art.

Advantageously, according to this embodiment, all pilot tracking occursbefore the FFT 304 operation, such that the phase error for subsequentsymbols, e.g., subsequent data symbols, is reduced prior to thesesubsequent OFDM data symbols being processed by the FFT 304. Thus, theoutput of the phase rotator 302 is routed to the pilot phase errormetric 808, which outputs an estimate of the aggregate phase error overthe entire OFDM data symbol. This estimate is used to update the loopfilter 314, which triggers the NCO 316 to rotate the phase of theincoming signal 116 for subsequent OFDM symbols.

The pilot phase error metric 808 is similar to the pilot phase errormetric 310 of FIG. 3, but includes respective discrete Fouriertransforms (DFTs) to generate complex signal measurements correspondingto each of the respective pilot subcarriers of the OFDM symbols. SeeFIG. 9 for more details on the pilot phase error metric 808. Thus, thepilot phase error metric 808 of FIG. 8 determines its own pilotreference points (u_(k) and v_(k)) and saves them. Then the pilot phaseerror metric 808 determines complex signal measurements (I_(k,m) andQ_(k,m)) corresponding to each of the pilot subcarriers of subsequentsymbols and processes them as the pilot phase error metric 310 of FIG.3.

However, since the pilot phase error metric 808 does not have to waitfor the FFT 304 operation to be complete, the pilot phase error metric808 may generate an aggregate phase error almost immediately afterreceiving the last time sample of the baseband signal 810 for a givensymbol. This reduces the time delay within the pilot tracking loop,which will increase the allowable closed-loop bandwidth. In contrast,the FFT 304 of FIGS. 3 and 8 waits until it receives all of the samplesof the given OFDM symbol, e.g., given OFDM data symbol, to beginprocessing them.

Referring next to FIG. 9, a functional block diagram is shown of thepilot phase error metric of the pilot tracking loop of FIG. 8 using amaximum likelihood estimation performed in accordance with oneembodiment of the invention. Shown is the pilot phase error metric 808including a discrete Fourier transform portion 901 (hereinafter referredto as DFT portion 901), multiplexers 402 and 404, a maximum likelihoodphase error/weighting processor 406, a quality estimator 408, a phaseerror estimator 410, and a random pilot modulation removal 412. The DFTportion 901 includes DFTs 902, 904, 906 and 908 (each of which may bereferred to generically as Fourier transforms). Also shown are the PNpilot modulation generator 312 and the reference point storage 308,which includes a u_(k) storage 44 414 and a v_(k) storage 416.

In operation, the pilot phase error metric 808 of FIG. 9 works similarlyto the pilot phase error metric 310 of FIG. 4. However, rather thanrelying on the FFT to determine the respective pilot reference pointsu_(k) and v_(k) and to determine the complex signal measurements for them^(th) subsequent data symbol I_(k,m) and Q_(k,M), these values aredetermined in the DFT portion 901 by respective ones of DFTs 902, 904,906 and 908. Each of these DFTs is configured to process the respectivepilots of the OFDM waveform. For example, according to one embodiment,during the long symbol portion of the OFDM of the preamble, DFT 902determines the complex signal measurements in rectangular form for pilot#0 (i.e., DFT 902 determines and v₀), DFT 904 determines the complexsignal measurements in rectangular form for pilot #1 (i.e., DFT 904determines u₁ and v₁), DFT 906 determines the complex signalmeasurements in rectangular form for pilot #2 (i.e., DFT 906 determinesu₂ and v₂), and DFT 908 determines the complex signal measurements inrectangular form for pilot #3 (i.e., DFT 908 determines u₃ and v₃).These values of u_(k) and v_(k) are stored in the reference pointstorage 308, i.e., in the u_(k) storage 414 and a v_(k) storage 416. Itis noted that the reference point storage 308 is not shown in FIG. 8.This reference point storage 308 may be embodied within the pilot phaseerror metric 808 or separately, as shown, such that the reference pointstorage 308 couples to the pilot phase error metric 808. With respect toStep 602 of FIG. 6, respective ones of DFTs 902, 904, 906 and 908, notthe FFT operation of the OFDM receiver, determine the pilot referencepoints for each of a plurality of k pilots. As described with referenceto FIG. 4, these pilot reference points are saved for use in the maximumlikelihood phase error/weighting processor 406.

Next, as the subsequent data symbols of the OFDM MAC frame are received,the pilot tracking loop 806 is activated. As such, complex signalmeasurements are determined by the DFT portion 901 using respective onesof DFTs 902, 904, 906 and 908 for each of the plurality of pilots forthe subsequent symbols, e.g., subsequent data symbols, rather than usingthe FFT operation. Thus the DFTs 902, 904, 906 and 908 determine thecomplex signal measurements (I_(k,m) and Q_(k,m)) corresponding to eachof the pilot subcarriers of subsequent symbols. Once these values ofI_(k,m) and Q_(k,m) are determined, they are coupled to multiplexers 402and 404 and processed by the maximum likelihood phase error/weightingprocessor 406, the phase error estimator 410 and the random pilotmodulation removal 412 as described with reference to FIGS. 4 and 6 inorder to produce an estimate of the aggregate phase error of theprocessed data symbol, {circumflex over (θ)}_(m). Thus, the phase errormetric 808 also follows the same steps as recited in FIG. 6; however,Steps 602 and 606 are performed by the DFT portion 901, instead of FFT304.

It is noted that in some embodiments, the data portion of the MAC framemay be much longer in duration than that specified in IEEE 802.11a. Insuch cases, it may be necessary to obtain and store updated pilotreference points at one or more locations within the data portion inaddition to or in place of pilot reference points obtained from thepreamble portion of the MAC frame. For example, at a specified symbol(e.g., data symbol) within the data portion, the complex measurementsobtained for the pilots of a particular OFDM data symbol are stored aspilot reference points, replacing the pilot reference points previouslyobtained during the preamble portion of the OFDM waveform. Thus, in Step602 of FIG. 6, the pilot reference points may be obtained from thepilots of an OFDM symbol, e.g., an OFDM data symbol, within the dataportion of the MAC frame. Next, the complex signal measurements of thepilots of subsequent OFDM symbols, e.g., subsequent OFDM data symbols,are compared to the pilot reference points obtained from within the dataportion of the MAC frame.

In this embodiment, since the pilot phase error metric 808 does not haveto wait for the FFT 304 operation to be complete, the pilot phase errormetric 808 generates an aggregate phase error almost immediately afterreceiving the last time sample of the baseband IQ signal output from thephase rotator 302 for a given symbol. This reduces the time delay withinthe pilot tracking loop, which will increase the allowable closed-loopbandwidth. In contrast, the FFT 304 of FIGS. 3 and 8 waits until itreceives all of the samples of the given OFDM data symbol to beginprocessing them. According to one embodiment, the time delay from thearrival of the last input sample pair (I,Q) of the current OFDM symbolinto the pilot phase error metric 808 to the computation of the outputof the phase error metric 808, {circumflex over (θ)}_(m), should be lessthan or equal to 10 clocks at 40 MHz. Ideally, the total transport delaythrough the pilot phase error metric 808 should be kept to less than 10%of an OFDM symbol, i.e., about 0.40 μsec. Advantageously, thisrepresents a significant savings in time as compared to using the outputbins of the FFT as described with reference to FIGS. 3-5.

It is noted that in some embodiments, the pilot phase error metric 808of FIG. 8 and the pilot phase error metric 310 of FIG. 3 may employother metrics to track the phase error of the OFDM data symbols. Forexample, rather than determining an aggregate phase error estimate ofthe current OFDM data symbol relative to the pilot reference points foreach of the pilots of the preamble or for each of the pilots of a datasymbol within the data portion of the MAC frame, a phase error estimatemay be determined by tracking the pilots of the current OFDM data symbolrelative to the strongest pilot of the preamble. Even such pilot phaseerror metrics when applied in the pilot tracking loops of FIGS. 3 and 8are a departure from the known art since the phase rotation is appliedto the incoming signal for subsequent OFDM data symbols prior to beinginput into the FFT operation of the OFDM receiver.

Referring next to FIG. 10, a functional block diagram is shown of oneembodiment of the DFT portion 901 of the phase error metric of FIG. 9.Illustrated is the DFT portion 901 including the baseband signal 810input into correlation processors 1002 and 1003, sign reversal modules1004 and 1005, and Integrate and dump modules 1006 and 1007.

In correlation processor 1002, the inphase (I) and quadrature (Q) termsof the baseband signal 810 are correlated with the respective ones ofthe sine and cosine of the output of a numerically controlled oscillator1010 at 7 ΔF (hereinafter referred to as NCO 1010) at multipliers 1012,1014, 1016, and 1018. The outputs of multipliers 1012 and 1014 aresummed at summation 1020, while the output of multiplier 1014 issubtracted from the output of multiplier 1012 at summation 1022. Theoutputs of multipliers 1016 and 1018 are summed at summation 1024, whilethe output of multiplier 1016 is subtracted from the output ofmultiplier 1018 at summation 1026.

Similarly, in correlation processor 1003, the inphase (I) and quadrature(Q) terms of the baseband signal 810 are correlated with the respectiveones of the sine and cosine of the output of a numerically controlledoscillator 1011 at 21 ΔF (hereinafter referred to as NCO 1011) atmultipliers 1028, 1030, 1032, and 1034. The outputs of multipliers 1028and 1030 are summed at summation 1036, while the output of multiplier1030 is subtracted from the output of multiplier 1028 at summiation1038. The outputs of multipliers 1032 and 1034 are summed at summation1040, while the output of multiplier 1032 is subtracted from the outputof multiplier 1034 at summation 1042.

As is easily seen due to symmetries in the pilot tone frequencies, thenumber of discrete DFTs is reduced from 4 to 2. That is, the number ofNCOs and complex cross multiplies is reduced from 4 to 2 in thecorrelation processors 1002 and 1003. Since the pilots are located at ±7and ±21 times the basic subearrier spacing ΔF (e.g., 312.5 kHz), theNCOs 1010 and 1011 operate at 7ΔF and 21ΔF respectively and the negativefrequencies are realized by using different signs in the additionprocesses (e.g., respective ones of summations 1020, 1022, 1024, 1026,1036, 1038, 1040 and 1042) that immediately follow the multiplications(e.g., at respective ones of multipliers 1012, 1014, 1016, 1018, 1028,1030, 1032 and 1034). Since these two frequencies (i.e., 7ΔF and 21ΔF)are known a priori, and they are tied to the symbol timing, the outputsof NCOs 1010 and 1011 are straight forward known number sequences.

Next, polarity differences between the pilot tones due to the randombi-phase modulation (e.g., BPSK) that is imposed on the OFDM pilotsubcarriers are removed using respective ones of sign reversalmultipliers 1044, 1046, 1048, 1050, 1052, 1054, 1056 and 1058 of thesign reversal modules 1004 and 1005. This is due to the fact thatdepending on various modes, the polarity of all the pilot tones is notnecessarily +1. For example, the polarity of one or more pilot tones maybe set to +1 while the polarity of others of the pilot tones may be setto −1. Since these polarities are known a priori, they are corrected atthe sign reversal modules 1004 and 1005. This ensures that the removalof the random bi-phase modulation of the pilot subcarriers for thesubsequent data symbols can be easily done at the conclusion of thepilot phase error metric 808, e.g., by the random pilot modulationremoval 312 of FIG. 8.

As such, the output of summations 1026 and 1020 are multiplied at signreversal multipliers 1044 and 1046, respectively, by S₀; the output ofsummations 1024 and 1022 are multiplied at sign reversal multipliers1048 and 1050, respectively, by S₁; the output of summations 1042 and1036 are multiplied at sign reversal multipliers 1052 and 1054,respectively; by S₂; and the output of summations 1040 and 1038 aremultiplied at sign reversal multipliers 1056 and 1058, respectively, byS₃. The values of S₀-S₃ are either ±1 depending on the specific systemdesign. It is noted that if all of the pilot tones have the samepolarity, e.g., +1, the sign reversal modules 1004 and 1005 are notneeded. It is noted that the sign reversal modules 1004 and 1005 couldoccur either before the correlation processors 1002 and 1003, or afterthe respective Integrate and dump modules 1006 and 1007; however, thelocation was chosen in order to minimize the number of gates forimplementation.

Next, the outputs of sign reversal modules 1004 and 1005 (or respectivesummations of the correlation processors 1002 and 1003, if no signreversing is required), are input to integrate and dump modules 1006 and1007. Each signal is input to a respective one integrators 1060, whichis then input to a respective one of shifters 1062. The number ofsamples summed In the Integrators 1060 depends on whether the longsymbols T₁ and T₂ of the long symbol portion 208 are being summed in thechannel estimation (accumulating 2×3.2 μsec or 128 samples at 20 MHz (or256 samples at 40 MHz)), i.e., Ch Est in FIG. 10, in order to determinethe pilot reference points u_(k) and v_(k), or whether the subsequentpilot symbols are being received to determine the I_(k,m) and Q_(k,m)values (accumulating 3.2 μsec or 64 samples at 20 MHz (or 128 samples at40 MHz)), i.e., Dat Sym in FIG. 10. Thus, the number of samples summedin the integrators 1060 depends on whether the DFT portion 901 isdetermining the pilot reference points (Step 602 of FIG. 6) or whetherthe DFT portion 901 is determining the complex signal measurements foreach of the pilots of a subsequent data symbol (Step 606 of FIG. 6),Additionally, the shifters 1062 dump a number of bits from 0 to 2depending on the clock rate, the type of symbol (e.g., channelestimation symbol (Ch Est) or data symbol (Dat Sym)), and the type ofconstellation type or modulation.

As is know, the integrate and dump modules 1006 and 1007 should besynchronized with the period of time recognized by the receiver as theactive portion of the received OFDM symbol, and accumulation only occursover this interval, e.g., a 3.2 μsec window. The accumulation windowshould be similarly aligned in time with the channel estimation process,precisely in-synch with the FFT channel estimation process that isoccurring in parallel at the channel estimator 804 of FIG. 8.

Thus, the DFT portion 901 outputs either the pilot reference pointsu_(k) and v_(k) or the complex signal measurements for the m^(th)subsequent data symbol I_(k,m) and Q_(k,m). Thus, there Is a respectiveOFT bin output for each of the plurality of pilots of the OFDM waveform.For example, as illustrated in FIG. 10, there is a separate DFT binoutput for the pilots at +7ΔF, −7ΔF, +21ΔF and −21ΔF. These outputs arecoupled to either the reference point storage 308 or one of multiplexers402 and 404 as shown in FIG. 8.

It is noted that the functionality and design of the correlationprocessors 1002 and 1003, the sign reversal modules 1004 and 1005 andthe integrate and dump modules 1006 and 1007 components of the DFTportion 901 of the phase error metric 808 are well understood in theart. It is also noted that the DFT portion 901 represents one embodimentof the DFT portion 901 including DFTs 902, 904, 906 and 908 of FIGS. 9.It is further noted that one of ordinary skill in the art could easilymodify the DFT portion 901 to achieve slightly different resultsdepending on the implementation.

Referring next to FIG. 11, an illustration is shown of the closed-looptransfer functions of the pilot tracking loop 806 of FIG. 8. The LOphase noise transfer function 1104 and the pilot tracking loop phasenoise transfer function 1102 are illustrated, when the update rate is250 kHz (i.e., 1/4.0 μsec), and when ω_(n)T=1 (i.e., ω_(n) is about 13.9kHz) and a damping factor ζ=0.75 are selected. It is noted that thisillustration does not include additive Gaussian noise. This choice alsocorresponds to the maximum closed-loop bandwidth achievable in thesampled control pilot tracking loop. For example, the maximum usageclosed-loop bandwidth is approximately 40 kHz for the 250 kHz OFDMsymbol rate (of the IEEE 802.11a and HyperLAN2 standards) without theadditional delay, in comparison to the maximum usable closed loopbandwidth of 15 kHz with the additional delay as shown in FIG. 7. Notethat the maximum closed-loop bandwidth is derived from the symbol rateof 250 kHz divided by 2π given an acceptable amount of delay. As can beseen, and in comparison to the illustration of FIG. 7, at frequencyoffsets of about 15 kHz, the noise peaking as shown in FIG. 7 issubstantially reduced. Thus, due to the increased tracking loopbandwidth, the pilot tracking loop 806 of FIG. 8 is sufficient to trackand reduce local oscillator phase noise at small frequency offsets, aswell as at larger frequency offsets.

Referring next to FIG. 12, a graph is shown illustrating the LO phasenoise contribution vs. frequency using no pilot tracking, pilot trackingaccording to the embodiment of FIGS. 3 through 4 and pilot trackingaccording to the embodiments of FIGS. 8 through 10. Line 502 representsthe LO phase contribution spectrum without pilot tracking techniquessynthesized at 4 GHz. Note that the graphs of FIG. 5 and FIG. 12 do notinclude channel additive Gaussian noise. For example, it is estimatedthat in one embodiment where the radio portion is highly integrated, theachievable phase noise performance in a free running on-chip VCO will beapproximately −78 dBc/Hz at 10 kHz offset. Thus, with the IEEE 802.11awaveform, according to one embodiment, the integrated phase noiseinterfering with each subcarrier is on the order of 2.7 degrees rms,which is excessive for 64-QAM and above. Generally, according to oneembodiment, the achievable phase noise performance in a free runningon-chip VCO is typically greater than about −80 dBc/Hz at 10 kHz offset,which results in an integrated phase noise interfering with eachsubcarrier of greater than 2.5 degrees rms.

Line 504 represents the phase noise contribution spectrum of the LO ofthe radio portion with the pilot phase tracking of the embodiment ofFIGS. 3 through 4 as described above, such that the phase noisecontribution is significantly reduced, particular at lower frequencyoffsets. It is also seen that at higher frequency offsets, e.g., between10 kHz and 100 kHz, the phase noise actually worsens in comparison tonot using any pilot tracking techniques. It is also noted that as theclosed loop tracking bandwidth is increased in the pilot tracking loopof FIGS. 3 and 4, more and more instability results due to additionaldelay added. Although not illustrated in FIG. 12, this results in aneven more pronounced phase noise peaking at about 25-30 kHz incomparison to that shown in line 504.

Line 1202 represents the phase noise contribution spectrum of the LO ofthe radio portion with the optimum pilot phase tracking of theembodiment of FIGS. 8 through 10 as described above, such that the phasenoise contribution is also reduced, in comparison to no pilot trackingtechniques and also in comparison to the phase noise contribution of thepilot phase tracking of FIGS. 3 through 4. In particular, the peakingshown in line 504 is reduced at higher frequency offsets, more closelyresembling line 502 at frequency offsets greater than about 11 kHz.Thus, as can be seen, the phase noise performance in a free runningon-chip VCO will be approximately −85 dBc/Hz at a 10 kHz frequencyoffset. Thus, according to this embodiment, the integrated phase noiseis advantageously reduced from about 2.7 degrees rms to about 0.48degrees rms using the pilot tracking loop of FIG. 8. According to someembodiments, the integrated phase noise may be reduced from greater thanabout 2.5 degrees rms to less than about 1 degree rms, and morepreferably, less than 0.5 degrees rms. This improvement in the phasenoise makes it possible to reduce the requirements on the radio's LOphase noise performance. This improvement also makes it possible tosupport higher order modulations, such as MPSK and M-ary QAM, e.g.,QPSK, 16-QAM, 64-QAM, 128-QAM, or higher.

Referring next to FIG. 13, a functional block diagram is shownillustrating the loop filter of the pilot tracking loop of FIG. 8according to one embodiment of the invention. Illustrated are a signaldecryption module 1302, the incoming signal 116 (which is a basebandsignal in this embodiment), an NCO/phase rotator 1304 outputtingbaseband signal 810, the phase error metric 808, the loop filter 314,coarse/fine frequency estimate signal 320 and a summation 318. Alsoshown are path A and path B for the baseband signal 810.

Although the loop filter 314 is illustrated for the embodiment of FIG.8, these details of the loop filter also apply to the embodiment of FIG.3. It is noted that the signal decryption module 1302 is shown in FIG.13, although not illustrated in FIG. 8. Thus, according to thisembodiment, the incoming signal 116 received into the NCO/phase rotator1304 has already been decrypted. Furthermore, in this illustration, forsimplicity, the NCO and phase rotator functional blocks of FIG. 8 arecombined into the NCO/phase rotator module 1304.

The loop filter 314, illustrated as a closed-loop tracking filterfunctions as a digital phase lock loop that tracks out small frequencyerrors remaining after the coarse and fine frequency estimation stepsperformed, for example, by the channel estimator 804 of FIG. 8. Asdescribed above, the input to the loop filter 314 is an estimate of theaggregate phase error of the processed data symbol relative to theaverage pilot phase of the pilot reference points, {circumflex over(θ)}_(m). In this embodiment, the loop filter 314 (and the NCO/phaserotator module 1304) is clocked at sampling rates of 20 MHz or 40 MHzand the loop filter 314 outputs 20-bit words (19.07 Hz/lsb at 20 MHz or38.15 Hz/lsb at 40 MHz). Since the pilot phase error metric 808 and theloop filter track relatively small frequencies, the coarse/finefrequency estimate signal 320 (from the channel estimation processduring the long symbols of the preamble) is summed with the output ofthe loop filter 314 at summation 318. The resulting output to theNCO/phase rotator module 1304 updates the NCO and causes the phaserotator to de-rotate the phase of the incoming baseband signal 116 inorder to reduce phase error and noise over the symbols of the OFDM MACframe.

Referring next to FIG. 14, a functional block diagram is shown of adigital implementation of the loop filter of FIG. 13 according toanother embodiment of the invention. Illustrated are the pilot phaseerror metric 808, multiplier 1402, summations 1404 and 1406, bitshifters 1408 and 1410, and z-transform 1412. In this embodiment, thez-transform 1412 is a simple one clock delay. The output of the phaseerror metric 808 (or optionally, phase error metric 310) is multipliedat multiplier 1402 with digital parameters K_(1f)*K_(1d), to produce adigital phase lock loop proportional term 1414, where digital parameterK_(1f)=1 at 40 MHz (K_(1f)=2 at 20 MHz) and digital parameter K_(1d) isderived by setting the loop natural frequency On and the damping factorζ at desired values and then computing the digital gains to achieveequivalent loop filter outputs for the digital implementation ascompared to a classical analog PLL response.

In parallel to determining the proportional term 1414, the output of thephase error metric 808 is input to bit shifter 1408 (which is a leftshifter), which shifts the input word by K_(2d) _(—) _(shift)+K_(2s),where digital parameter K_(2s) is 0 at 40 MHz or 2 at 20 MHz, anddigital parameter K_(2d) _(—) _(shift) is derived by setting the loopnatural frequency ω_(n) and the damping factor ζ at desired values andthen computing the digital gains to achieve equivalent loop filteroutputs for the digital implementation. The output of bit shifter 1408is summed at summation 1406 with the output of the summation 1406 asoutput from z-transform 1412 (e.g., one clock delay) and fed back intosummation 1406. Also, the output of summation 1406 is also input to bitshifter 1410 (which is a right shifter) in order to produce the digitalphase lock loop integral term 1416. The integral term 1416 is summedwith the proportional term 1414 at summation 1404 to produce the loopfilter output 1418.

The fixed-point Q numbers illustrated in FIG. 14 indicate the number ofbinary bits and the position of their relative binary points. Any changein the Q format after an operation implies truncation of the leastsignificant bits after the binary points (the fractional part) anddropping the most significant bits before the binary point (the integerpart) while preserving the msb sign bit. For example, the Q format forthe product the output of the phase error metric 808 and K_(1f)^(*)K_(1d) at multiplier 1402 is 16Q15t*12QOu or 28Q15t and is convertedto 15Q2t by truncating 13 Isbs. Another example is the summation of theproportional term 1414 (15Q2t) and the integral term 1416 (16Q2t) atsummation 1404 results in 16Q2t number and is converted to 14QOt bydropping 2 lsbs. Rounding and saturation are assumed in theseconversions.

The phase detector gain K_(dd) is such that the a full-scale error of180 degrees yields a unity output, and the NCO step size K_(vd) is givenby ${K_{vd} = {2{\pi \left( \frac{F_{s}}{2^{20}} \right)}}},$

where F_(s) is 40 MHz or 20 MHz, for example. Under these conditions,the digital gains K₁ and K₂ are given by: $\begin{matrix}{K_{1} = {\omega_{n}{\zeta \left( \frac{K_{vd}}{2\pi} \right)}^{- 1}}} & {{Eq}.\quad (19)} \\{K_{2} = {\pi \quad {T_{s}\left( \frac{\omega_{n}^{2}}{K_{vd}} \right)}}} & {{Eq}.\quad (20)}\end{matrix}$

where ω_(n) is the natural loop frequency, ζ is the damping factor,K_(vd) is the NCO step size, and T_(s) is F_(s) ⁻¹.

For ζ=0.5, ω_(n)=2π4000 Hz, K_(v)=2·π·100 ·10³ and K_(d)=1, andapproximately 69.813 Hz per 1° phase error, which corresponds to32768/180 at the input to the loop filter, the digital proportional term1414 output is:

K_(1d)=329 in 12Q0u

${{1{^\circ}\quad {phase}\quad {error}} \equiv \frac{32768}{180}} = {182\quad {in}\quad 16Q\quad 15t}$${{Proportional}\quad \left( {1{^\circ}\quad {phase}\quad {error}} \right)} = {{182 \cdot 329} = {{{{598\quad {in}\quad 28Q\quad 15t}\quad \overset{{truncate}\quad 3\quad {lsbs}}{\rightarrow}\quad 7.3}->{{{7\quad {in}\quad 15Q\quad t}\overset{{truncate}\quad {lsbs}\quad {and}\quad {drop}\quad 4\quad {msbs}}{\rightarrow}\quad 1.75}->{{2\quad {in}\quad 9Q\quad 0t} \approx {{2 \cdot 38.15}\quad {Hz}}}}} = {76.3\quad {Hz}}}}$

A subset of the possible settings for the loop filter digital parametersK₁ and K₂ for operation at a sampling rate of 40 MHz are shown in Table1 below. Digital parameter K_(1d) is the rounded K₁ value representingwith 13-bit unsigned number (13Q0u) in the fixed-point implementation.Digital parameter K_(2d) is a fixed point representation of K₂*16 androunded to the closest power of 2's so that the multiplier on theintegral path can be implemented with the left bit shifter 1408 asindicated in Table 1 by K_(2d) _(—) _(shift). At the 20 MHz rate, the K₁and K₂ values are as given in Table 1 except that they must bemultiplied by factors of 2 and 4, respectively. In this embodiment, theoutput 1418 of the digital implementation of the loop filter 314 hasresolution of $\frac{F_{s}}{2^{20}}$

Hz per lsb.

It is noted that the loop filter 314, such as the digital implementationillustrated in FIG. 14 is operated under processor control. Thus, theprocessor controlling the loop filter selects the appropriate digitalparameters to ensure the best operation of the pilot phase trackingloop. It is further noted that the loop filter and the determination ofthe respective digital parameters as described herein is well understoodin art.

TABLE 1 K_(1d) K₂*16 ω_(n)/2π ζ K₁ (13Q0u) K₂ (Q4) K_(2d)__(shift) 0 2000 Hz 0.50 167.71 168 0.05175 0.8 <<0 1  2000 Hz 0.707 232.90 2330.05175 0.8 <<0 2  2000 Hz 0.90 296.48 294 0.05175 0.8 <<0 3  4000 Hz0.50 329.42 329 0.20698 3.31 <<2 4  4000 Hz 0.707 465.8 466 0.20698 3.31<<2 5  4000 Hz 0.90 592.96 593 0.20698 3.31 <<2 6  6000 Hz 0.50 494.13494 0.46571 7.45 <<3 7  6000 Hz 0.707 698.7 699 0.46571 7.45 <<3 8  6000Hz 0.90 889.43 889 0.46571 7.45 <<3 9  8000 Hz 0.50 658.84 659 0.8279213.25 <<4 10  8000 Hz 0.707 931.6 932 0.82792 13.25 <<4 11  8000 Hz 0.901185.91 1186 0.82792 13.25 <<4 12 10000 Hz 0.50 823.55 824 1.29363 20.7<<4 13 10000 Hz 0.707 1164.5 1165 1.29363 20.7 <<4 14 10000 Hz 0.901482.39 1482 1.29363 20.7 <<4 15 Res. Res. Res. Res. Res. Res. Res. 31Res. Res. Res. Res. Res. Res. Res.

Referring next to FIG. 15, a functional block diagram is shownillustrating a simulated version of the digital loop filter of FIG. 14.Illustrated is the pilot phase error metric 1502, multipliers 1502 and1504, summations 1506, 1508 and 318, and z-transform 1512. Also shownare the probe points in the simulation, i.e., the pilot phase errormetric 1520, the DPLL proportional 1514, the DPLL Integral 1516 and theDPLL output 1518. The simulation was done using a fixed point Matlabsimulation. The results of the simulation at the probe points areplotted in FIG. 16 for an initial frequency offset of 1000 HZ withω_(n)=2π4000 Hz, ζ=0.5, K_(1d)=329^(*)2 and K_(2d) _(—) _(shift)=2+2 ata 20 MHz rate. Line 1602 represents the output of the pilot phase errormetric 1520, line 1604 represents the DPLL proportional 1514, line 1606represents the DPLL Integral 1516 and line 1608 represents the DPLLoutput 1518 after being summed with the coarse/fine frequency estimatesignal 320 at the summation 318.

Thus, for a step change in frequency of about 1000 Hz, it can be seenthat the transient peak time of occurrence is approximately 48.12 sec or962 samples at 20 MHz and the peak phase error is approximately 7.8°. Itis noted that in operation, the actual peak time of the phase errormetric will be longer than 962 samples because the loop filter does notrun during the guard interval of the OFDM symbol. Thus, as can be seenin the simulation, the pilot tracking loop quickly acquires the initialfrequency error thereby eliminating frequency errors prior to the FFT inthe OFDM receiver.

Referring briefly to FIG. 1, frequency pulling (due to slight impedancechanges imposed on the output of the main local oscillator frequencysynthesizer or LO 108) and frequency pushing (due to primarily slightD.C. supply changes resulting from current load changes ) can result inserious frequency errors particularly at the beginning of a user's timeslot. Frequency pulling is a frequency error primarily caused by theswitching of the OFDM transceiver between transmit and receiveoperations. It is noted that although FIG. 1 illustrates the OFDMreceiver 100, the OFDM receiver 100 may be a part of an OFDM transceiverincluding an OFDM transmitter. Such an OFDM receiver and OFDMtransmitter may be integrated into one or more devices and togethercomprise the OFDM transceiver. Frequency pushing is a frequency errorthat arises from power supply noise or contamination. Frequency pushingis most problematic at frequencies on the order of the natural loopfrequency ω_(n) of the pilot tracking loop. It is noted that theconcepts of frequency pulling and frequency pushing are well understoodin the art. Furthermore, as described above, the total frequency errorbetween an OFDM transmitter (not shown) and the OFDM receiver 100 shouldbe on the order of 100 Hz or less for 64-QAM or higher modulationoperation. This is a stringent requirement according to preferredembodiments where the operational frequency is in the 5 GHz range and100 Hz represents roughly 0.02 parts-per-million (ppm). Thus, ideally,frequency pulling and frequency pushing occurring at the beginning of anOFDM MAC frame should be kept to the 100 Hz maximum.

The pilot tracking loops are described above with reference to FIGS.2-16 are designed to reduce phase/frequency errors by tracking thepilots of the OFDM waveform. Thus, at lower frequency offsets, the pilottracking loop (e.g., pilot tracking loops 300 and 806 in the basebandprocessing 106 portion) adequately reduces this effect. However, incases where frequency pulling and frequency pushing cause a frequencyerror greater than 100 Hz, the pilot tracking loop may be furthermodified to minimize this effect.

Since frequency pulling and frequency pushing primarily occur at thebeginning of a time slot, and according to one embodiment of theinvention, the closed loop bandwidth of the pilot tracking loop isoperated wider than the nominally designed closed loop trackingbandwidth at the front end of the time slot when receiving OFDM datasymbols in order to minimize the phase tracking error due to thefrequency transient. Then, the closed loop bandwidth of the pilottracking loop is subsequently reduced later in the time slot to thenominally designed closed loop tracking bandwidth once the frequencyerror has been adequately contained. Generally, widening the closed loopbandwidth improves the frequency error pull-in time and frequencypulling and pushing issues of the pilot tracking loop up to a point, butit also allows more Gaussian noise contribution to fall within the pilottracking loop.

In some embodiments, the RF frequency pushing and pulling are kept tothe 100 Hz maximum. The PTL is designed such that it can be used tomitigate frequency pushing and pulling problems at the beginning of auser burst if this objective is not met. In doing this, the PTLclosed-loop bandwidth can be increased at the front-end of the time slotin order to minimize the phase tracking error due to the frequencytransient and the bandwidth subsequently reduced later in the time slotonce the frequency error has been adequately contained. The largerbandwidth will result in poorer performance due to Gaussian channelnoise however, so the degree of bandwidth expansion used must be chosento optimize the overall result.

Generally, the parameters of the pilot tracking loops 300 and 806 aredesigned to minimize the overall quantity given by

θ_(Tot)=θ_(Transient)+η{square root over (θ² _(AWGN)+θ² _(LO))}  Eq.(21)

where θ_(Transient) is the peak phase transient caused by any initialfrequency error at the beginning of a user burst, θ_(AWGN) is theGaussian rms noise contribution from the receive channel that fallswithin the PTL noise bandwidth, and θ_(LO) is the phase noisecontribution from the transmitter and receiver local oscillators thatstill remains after clean-up by the PTL. In Eq. (21), η is a confidencefactor that should be taken to be in the range of 1.0 to 3.0.

The choice of PTL parameters that minimize θ_(Tot) of Eq. (21) primarilydepend upon (a) the received signal SNR, (b) the phase noise spectrum ofthe transmitter and receiver local oscillators, and (c) the amount ofinitial frequency error that must be handled at the beginning of eachtime slot. If for a given scenario an acceptably small θ_(Tot) cannot beachieved relative to the signal constellation type being used (e.g.,16-QAM), the net result is a loss of receiver sensitivity. Thus, as canbe seen in Eq. (21), the effect of increasing the closed loop trackingbandwidth is an increase in the total phase error. Thus, once theeffects of frequency pulling and frequency pushing are sufficientlyreduced, the closed loop bandwidth of the pilot tracking loop isreduced. This allows for the OFDM transceiver to be able to supportcommunications of at least QPSK modulation (i.e., 4-ary QAM) or higher,e.g., 16-QAM, 64-QAM, etc.

Referring next to FIG. 17, a flowchart is shown of the steps performedto reduce the effects of frequency pulling and frequency pushingaccording to another embodiment of the invention. Initially, the OFDMreceiver detects the beginning of an OFDM MAC frame (Step 1702). Thepreamble of the MAC frame is processed as described above. Normally,once the preamble is finished and the OFDM data symbols are received inthe data portion of the MAC frame, the pilot tracking loop is activated,such that the pilot tracking loop has a nominal closed loop trackingbandwidth.

According to one embodiment, if it is determined that frequency pullingand frequency pushing are causing a frequency error between receive andtransmit operations greater than a specified amount (e.g., 100 Hz inthis embodiment), the closed loop tracking bandwidth operated at aclosed loop tracking bandwidth that is greater than the nominal closedloop tracking bandwidth during a specified number of OFDM data symbolsat the beginning of the data portion of the MAC frame (Step 1704). It isnoted that the amount of the increase in the closed loop bandwidth abovethe nominal closed loop tracking bandwidth and the number of datasymbols that the increased bandwidth is used varies depending on therequirements of the particular system. Furthermore, it is noted thatoperating the bandwidth above the nominally designed closed looptracking bandwidth for a given system is normally not desirable sincethis allows for more Gaussian noise to be introduced into the pilottracking loop.

Next, after the specified number of OFDM data symbols, the closed looptracking bandwidth is subsequently reduced back to the nominal closedloop tracking bandwidth (Step 1706). With careful altering of the closedloop tracking bandwidth, the effects of frequency pulling and frequencypushing can be reduced, e.g., reduced such that the frequency errorbetween transmitter and receiver is less than the prescribed amount, (inthis case, reduced to less than 100 Hz). According to this embodiment,in order to minimize the additional Gaussian noise contribution, theclosed loop bandwidth is returned to the nominal value. It is noted thataccording to this embodiment, the closed loop tracking bandwidth isaltered during the data portion of a single OFDM MAC frame. Again, theincrease in the bandwidth above the nominally designed closed looptracking bandwidth and the duration of increase will vary depending onthe system.

The steps of FIG. 17 are typically performed as a set of instructionsthat are performed in dedicated hardware or in software using aprocessor or other machine to execute the instructions to accomplish thegiven steps. For example, the steps of FIG. 17 are performed by thepilot tracking loop of the baseband processing portion of an OFDMreceiver as controlled by a processor or other component.

While the invention herein disclosed has been described by means ofspecific embodiments and applications thereof, numerous modificationsand variations could be made thereto by those skilled in the art withoutdeparting from the scope of the invention set forth in the claims.

What is claimed is:
 1. A pilot phase tracking loop for an orthogonalfrequency division multiplexed (OFDM) receiver comprising: a phaserotator for receiving an incoming signal; a Fourier transform coupled toan output of the phase rotator; a pilot phase error metric coupled to anoutput of the Fourier transform for determining a phase error estimateassociated with a received OFDM symbol; a loop filter coupled to anoutput of the pilot phase error metric; and an oscillator coupled to anoutput of the loop filter, the oscillator having an output coupled tothe phase rotator for causing the phase rotator to rotate the phase ofthe incoming signal by the filtered phase error estimate for subsequentOFDM symbols such that the phase noise of the signaling output from thephase rotator is reduced; wherein the pilot phase error metric uses amaximum likelihood estimation that processes complex signal measurementsfrom the Fourier transform corresponding to each of a plurality ofpilots of the received OFDM symbol in comparison to pilot referencepoints obtained from each of a plurality of pilots of a previous OFDMsymbol.
 2. The pilot phase tracking loop of claim 1 wherein the Fouriertransform comprises a fast Fourier transform.
 3. The pilot phasetracking loop of claim 1 wherein the pilot phase error metric uses themaximum likelihood estimation that processes the complex signalmeasurements from the Fourier transform corresponding to each of theplurality of pilots of the received OFDM symbol in comparison to thepilot reference points for each of the plurality of pilots of an OFDMpreamble waveform.
 4. The pilot phase tracking loop of claim 1 furthercomprising a pilot reference point storage coupled to the output of theFourier transform and coupled to the pilot phase error metric forstoring the pilot reference points corresponding to each of theplurality of pilots.
 5. The pilot phase tracking loop of claim 1 furthercomprising a pseudo random pilot modulation generator coupled to thepilot phase error metric for removal of a priori known pseudo-randompilot modulation.
 6. The pilot phase tracking loop of claim 1 furthercomprising a radio portion of the OFDM receiver that provides theincoming signal to the phase rotator, the radio portion including alocal oscillator, wherein the pilot phase tracking loop compensates forphase noise introduced by the radio portion and phase noise introducedby a transmitting radio portion of an OFDM transmitter communicatingwith the OFDM receiver.
 7. The pilot phase tracking loop of claim 1wherein a phase noise of the signaling output from the phase rotatorafter rotation is reduced.
 8. The pilot phase tracking loop of claim 7wherein the phase noise of the signaling output from the phase rotatorafter rotation is reduced to less than about 1 degree rms.
 9. The pilotphase tracking loop of claim 8 wherein the phase noise of the incomingsignal received at the phase rotator is less than about 2.5 degrees rms.10. The pilot phase tracking loop of claim 7 wherein the phase noise ofthe signaling output from the phase rotator after rotation is reduced toless than about 0.5 degrees rms.
 11. The pilot phase tracking loop ofclaim 10 wherein the phase noise of the incoming signal received at thephase rotator is less than about 2.5 degrees rms.
 12. The pilot phasetracking loop of claim 7 wherein the phase noise performance of a localoscillator of a radio portion of the OFDM receiver is greater than about−80 dBc/Hz at a 10 kHz offset.
 13. A pilot phase tracking loop for anorthogonal frequency division multiplexed (OFDM) receiver comprising: aphase rotator for receiving and adjusting the phase of an incomingsignal corresponding to an OFDM waveform; a Fourier transform coupled toan output of the phase rotator; a pilot phase error metric coupled to anoutput of the Fourier transform; a loop filter coupled to the pilotphase error metric; and an oscillator coupled to the loop filter andhaving an output coupled to the phase rotator; wherein the pilot phaseerror metric uses a maximum likelihood estimation that processes complexsignal measurements from the Fourier transform corresponding to each ofa plurality of pilots of an OFDM symbol in comparison to pilot referencepoints obtained from each of the plurality of pilots of a previous OFDMsymbol.
 14. The pilot phase tracking loop of claim 13 wherein theFourier transform comprises a fast Fourier transform.
 15. The pilotphase tracking loop of claim 13 further comprising a pilot referencepoint storage coupled to the output of the Fourier transform and coupledto the pilot phase error metric.
 16. The pilot phase tracking loop ofclaim 13 wherein the pilot phase error metric uses the maximumlikelihood estimation that processes the complex signal measurementsfrom the Fourier transform corresponding to each of the plurality ofpilots of the OFDM symbol in comparison to the pilot reference pointscorresponding to each of the plurality of pilots of an OFDM preamblewaveform.
 17. The pilot phase tracking loop of claim 13 furthercomprising a radio portion of the OFDM receiver that provides theincoming signal to the phase rotator, wherein the radio portion includesa local oscillator, wherein the pilot phase tracking loop compensatesfor phase noise introduced in the radio portion and phase noiseintroduced by a transmitting radio portion of an OFDM transmittercommunicating with the OFDM receiver.
 18. The pilot phase tracking loopof claim 17 wherein the phase noise of the incoming signal output fromthe phase rotator is reduced.
 19. The pilot phase tracking loop of claim18 wherein as a result of the reduced phase noise of the incomingsignaling output from the phase rotator, a phase noise performance ofthe OFDM receiver using M-ary QAM, M-PSK, and other digital modulationwaveforms is improved.
 20. A method for tracking pilot phase in anorthogonal frequency division multiplexed (OFDM) receiver comprising:receiving an incoming signal corresponding to an OFDM preamble waveformat a Fourier transform of the OFDM receiver; determining pilot referencepoints corresponding to a plurality of pilots of the OFDM preamblewaveform; receiving the incoming signal corresponding to an OFDM symbolat the Fourier transform; determining complex signal measurementscorresponding to each of the plurality of pilots of the OFOM symbol;determining a phase error estimate corresponding to the OFDM symbol;filtering the phase error estimate; and rotating a phase of the incomingsignal for subsequent OFDM symbols to be received at the Fouriertransform after the OFDM symbol by the filtered phase error estimate,wherein a phase noise of the incoming signal for the subsequent OFDMsymbols is reduced; wherein the determining the phase error estimatecomprises determining an aggregate phase error estimate of the OFDMsymbol relative to the pilot reference points using the complex signalmeasurements corresponding to each of the plurality of pilots of theOFDM symbol and the pilot reference points; and wherein the determiningthe aggregate phase error estimate step comprises performing a maximumlikelihood-based estimation using the complex signal measurements andthe pilot reference points.
 21. The method of claim 20 wherein thereceiving the incoming signal representing the OFDM preamble waveformcomprises receiving the incoming signal representing the OFDM preamblewaveform at a fast Fourier transform of the OFDM receiver.
 22. Themethod of claim 20 wherein the receiving the incoming signalrepresenting the OFDM symbol comprises receiving the incoming signalrepresenting the OFDM symbol at a fast Fourier transform.
 23. The methodof claim 20 further comprising updating an oscillator with the filteredphase error estimate, wherein the oscillator causes the rotating step.24. The method of claim 20 wherein the determining the aggregate phaseerror estimate Is represented mathematically as:${\hat{\theta}}_{m} = {\tan^{- 1}\left\lbrack \frac{\sum\limits_{k = 0}^{n - 1}\left( {{u_{k}Q_{k,m}} - {v_{k}I_{k,m}}} \right)}{\sum\limits_{k = 0}^{n - 1}\left( {{u_{k}I_{k,m}} + {v_{k}Q_{k,m}}} \right)} \right\rbrack}$

where {circumflex over (θ)}_(m) is the aggregate phase error for theOFDM symbol having a time index m, wherein u_(k) and v_(k) representin-phase (I) and quadrature (Q) values, respectively, for the pilotreference points for n pilots of the OFDM preamble waveform, and whereI_(k,m) and Q_(k,m) represent the complex signal measurementscorresponding to the k^(th) pilot of the m^(th) OFDM symbol.
 25. Themethod of claim 20 wherein the determining the pilot reference pointscomprises determining the pilot reference points corresponding to theplurality of pilots of a long symbol portion of the OFDM preamblewaveform.
 26. The method of claim 25 wherein the determining the pilotreference points and the complex signal measurements steps compriseprocessing the incoming signal corresponding to the long symbol portionand the incoming signal corresponding to the OFDM symbol with theFourier transform.
 27. A method of pilot phase tracking in an orthogonalfrequency division multiplexed (OFDM) receiver comprising: receiving anincoming signal representing an OFDM waveform at a Fourier transform ofthe OFDM receiver; determining a phase error estimate corresponding toan OFDM symbol of the OFDM waveform based upon the output of the Fouriertransform; filtering the phase error estimate; and rotating a phase ofthe incoming signal for subsequent OFDM symbols to be received at theFourier transform after the OFDM symbol by the filtered phase errorestimate, wherein the phase noise of the incoming signal for thesubsequent OFDM symbols is reduced; wherein the determining the phaseerror estimate step comprises determining an aggregate phase errorestimate of the OFDM symbol relative to a pilot phase corresponding to aprevious OFDM symbol; wherein the determining the phase error estimatestep further comprises: determining pilot reference points correspondingto a plurality of pilots corresponding to the previous OFDM symbol;determining complex signal measurements corresponding to the pluralityof pilots of the OFDM symbol; wherein the determining the aggregatephase error estimate includes processing the complex signal measurementsand the pilot reference points using a maximum likelihood-basedestimation.
 28. The method of claim 27 wherein the determining the phaseerror estimate comprises determining the aggregate phase error estimateof the OFDM symbol relative to the pilot phase corresponding to an OFDMpreamble portion of the OFDM waveform.
 29. The method of claim 28wherein the determining the phase error estimate step further comprises:determining the pilot reference points corresponding to the plurality ofpilots corresponding to the OFDM preamble portion of the OFDM waveform;determining the complex signal measurements corresponding to theplurality of pilots of the OFDM symbol; wherein the determining theaggregate phase error estimate includes processing the complex signalmeasurements and the pilot reference points using the maximumlikelihood-based estimation.